We are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.
You are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling.
You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators.
You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale.
You are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics.
You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear.
You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.
You have experience in computational biology or protein design. You have worked on ML-driven projects in biology.
You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.
Build machine learning models that work in the physical world [~90% of your time]:
Contribute to a careful curation of our training and evaluation data.
Propose and build ML evaluation metrics that align with real world success and company goals.
Quickly prototype generative models against our lead metrics and perform deep analyses of improvements.
Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
Contribute to the maintenance of our compute and ML development infrastructure.
In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.
Quickly learn from wet lab results and feedback data to our models.
Self development [~10% of your time]:
Stay on top of the latest developments in ML.
Gain a strong working understanding of protein and cell biology.
Participate in knowledge sharing, e.g. organize and present at our internal reading group.
Attend and present at conferences.
We offer strongly competitive compensation and benefits packages, including:
Private health insurance
Pension/401(K) contributions
Generous leave policies (including gender neutral parental leave)
Hybrid working
Travel opportunities and more
We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
","descriptionPlain":"THE OPPORTUNITY\n\nWe are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.\n\n\n\n\nWHO YOU ARE\n\n - You are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling.\n\n - You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators.\n\n - You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale.\n\n - You are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics.\n\n - You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear.\n You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.\n\n\n\n\nWHAT SETS YOU APART\n\n - You have experience in computational biology or protein design. You have worked on ML-driven projects in biology.\n\n - You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.\n\n\n\n\nYOUR RESPONSIBILITIES\n\n - Build machine learning models that work in the physical world [~90% of your time]:\n \n - Contribute to a careful curation of our training and evaluation data.\n \n - Propose and build ML evaluation metrics that align with real world success and company goals.\n \n - Quickly prototype generative models against our lead metrics and perform deep analyses of improvements.\n \n - Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.\n \n - Contribute to the maintenance of our compute and ML development infrastructure.\n \n - In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.\n \n - Quickly learn from wet lab results and feedback data to our models.\n\n - Self development [~10% of your time]:\n \n - Stay on top of the latest developments in ML.\n \n - Gain a strong working understanding of protein and cell biology.\n \n - Participate in knowledge sharing, e.g. organize and present at our internal reading group.\n \n - Attend and present at conferences.\n\n\n\n\nAPPLY\n\nWe offer strongly competitive compensation and benefits packages, including:\n\n - Private health insurance\n\n - Pension/401(K) contributions\n\n - Generous leave policies (including gender neutral parental leave)\n\n - Hybrid working\n\n - Travel opportunities and more\n\n\n\nWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.\n\n\n\nWe welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}},{"id":"6d9569d7-8fe4-43f0-bd57-476287666218","title":"Member of Technical Staff","department":"Foundation Models","team":"Foundation Models","employmentType":"FullTime","location":"San Francisco","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-02-19T09:02:52.631+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/latentlabs/6d9569d7-8fe4-43f0-bd57-476287666218","applyUrl":"https://jobs.ashbyhq.com/latentlabs/6d9569d7-8fe4-43f0-bd57-476287666218/application","descriptionHtml":"We are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.
You are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling.
You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators.
You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale.
You are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics.
You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear.
You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.
You have experience in computational biology or protein design. You have worked on ML-driven projects in biology.
You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.
Build machine learning models that work in the physical world [~90% of your time]:
Contribute to a careful curation of our training and evaluation data.
Propose and build ML evaluation metrics that align with real world success and company goals.
Quickly prototype generative models against our lead metrics and perform deep analyses of improvements.
Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
Contribute to the maintenance of our compute and ML development infrastructure.
In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.
Quickly learn from wet lab results and feedback data to our models.
Self development [~10% of your time]:
Stay on top of the latest developments in ML.
Gain a strong working understanding of protein and cell biology.
Participate in knowledge sharing, e.g. organize and present at our internal reading group.
Attend and present at conferences.
We offer strongly competitive compensation and benefits packages, including:
Private health insurance
Pension/401(K) contributions
Generous leave policies (including gender neutral parental leave)
Hybrid working
Travel opportunities and more
We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
","descriptionPlain":"THE OPPORTUNITY \n\nWe are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.\n\n\n\n\nWHO YOU ARE\n\n - You are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling.\n\n - You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators.\n\n - You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale.\n\n - You are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics.\n\n - You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear.\n You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.\n\n\n\n\nWHAT SETS YOU APART\n\n - You have experience in computational biology or protein design. You have worked on ML-driven projects in biology.\n\n - You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.\n\n\n\n\nYOUR RESPONSIBILITIES\n\n - Build machine learning models that work in the physical world [~90% of your time]:\n \n - Contribute to a careful curation of our training and evaluation data.\n \n - Propose and build ML evaluation metrics that align with real world success and company goals.\n \n - Quickly prototype generative models against our lead metrics and perform deep analyses of improvements.\n \n - Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.\n \n - Contribute to the maintenance of our compute and ML development infrastructure.\n \n - In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.\n \n - Quickly learn from wet lab results and feedback data to our models.\n\n - Self development [~10% of your time]:\n \n - Stay on top of the latest developments in ML.\n \n - Gain a strong working understanding of protein and cell biology.\n \n - Participate in knowledge sharing, e.g. organize and present at our internal reading group.\n \n - Attend and present at conferences.\n\n\n\n\nAPPLY\n\nWe offer strongly competitive compensation and benefits packages, including:\n\n - Private health insurance\n\n - Pension/401(K) contributions\n\n - Generous leave policies (including gender neutral parental leave)\n\n - Hybrid working\n\n - Travel opportunities and more\n\n\n\nWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.\n\n\n\nWe welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}},{"id":"21821a19-0f7a-4352-abe2-ac788fc33e0d","title":"Member of Technical Staff, Applied AI","department":"AI Integration","team":"AI Integration","employmentType":"FullTime","location":"London","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-02-20T18:44:24.826+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"United Kingdom","addressCountry":"United Kingdom","addressLocality":"London"}},"jobUrl":"https://jobs.ashbyhq.com/latentlabs/21821a19-0f7a-4352-abe2-ac788fc33e0d","applyUrl":"https://jobs.ashbyhq.com/latentlabs/21821a19-0f7a-4352-abe2-ac788fc33e0d/application","descriptionHtml":"Member of Technical Staff, Applied AI
We are looking for a Member of Technical Staff with deep expertise in generative modelling to work at the interface between our frontier models and the customers who depend on them. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will develop an in-depth understanding of our proprietary generative models and apply that knowledge to deploy, adapt and optimise them within customer environments - particularly in the pharmaceutical and biotech sectors.
This is a hybrid role. You will need a researcher’s depth of understanding of our models, combined with the pragmatism and communication skills to translate that understanding into production systems that deliver scientific value for our partners.
At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.
Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.
We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.
You are a strong ML researcher with experience in generative modelling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a deep understanding of generative model architectures, training dynamics and inference behaviour.
You are a skilful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.
You are customer-facing and delivery-oriented. You thrive in environments where customer success is the primary measure of your work. You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.
You are passionate about model performance. You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed. You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.
You are mission driven and curious. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment where you must context-switch between deep technical work and customer-facing engagements.
You have experience in computational biology or protein design. You have worked on ML-driven projects in biology and understand the unique data challenges, evaluation paradigms and scientific workflows of biological modelling.
You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime.
You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields, giving you an intuitive understanding of the scientific problems our customers are solving.
Develop, deploy and adapt our models for customer environments:
Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.
Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.
Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.
Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.
Ensure deployments meet customer standards for security, performance and reliability.
Customer partnership & product feedback:
Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.
Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.
In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.
Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.
Create technical documentation, integration guides and best-practice resources.
Spend time working on-site at international partner locations as needed.
Self development:
Stay on top of the latest developments in ML, model serving and cloud-native tooling.
Gain a strong working understanding of protein and cell biology.
Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
Participate in knowledge sharing, e.g. organise and present at our internal reading group.
Attend and present at conferences.
We offer strongly competitive compensation and benefits packages, including:
Private health insurance
Pension contributions
Generous leave policies (including gender neutral parental leave)
Hybrid working
Travel opportunities and more
We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
","descriptionPlain":"Member of Technical Staff, Applied AI\n\n\nTHE OPPORTUNITY\n\nWe are looking for a Member of Technical Staff with deep expertise in generative modelling to work at the interface between our frontier models and the customers who depend on them. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will develop an in-depth understanding of our proprietary generative models and apply that knowledge to deploy, adapt and optimise them within customer environments - particularly in the pharmaceutical and biotech sectors.\n\nThis is a hybrid role. You will need a researcher’s depth of understanding of our models, combined with the pragmatism and communication skills to translate that understanding into production systems that deliver scientific value for our partners.\n\n\n\n\nWHO WE ARE\n\nAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.\n\nOur team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.\n\nWe’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.\n\n\n\n\nWHO YOU ARE\n\n - You are a strong ML researcher with experience in generative modelling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a deep understanding of generative model architectures, training dynamics and inference behaviour.\n\n - You are a skilful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.\n\n - You are customer-facing and delivery-oriented. You thrive in environments where customer success is the primary measure of your work. You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.\n\n - You are passionate about model performance. You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed. You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.\n\n - You are mission driven and curious. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment where you must context-switch between deep technical work and customer-facing engagements.\n\n\nWHAT SETS YOU APART (PREFERRED, NOT REQUIRED)\n\n - You have experience in computational biology or protein design. You have worked on ML-driven projects in biology and understand the unique data challenges, evaluation paradigms and scientific workflows of biological modelling.\n\n - You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime.\n\n - You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields, giving you an intuitive understanding of the scientific problems our customers are solving.\n\n\nYOUR RESPONSIBILITIES\n\nDevelop, deploy and adapt our models for customer environments:\n\n - Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.\n\n - Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.\n\n - Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.\n\n - Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.\n\n - Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.\n\n - Ensure deployments meet customer standards for security, performance and reliability.\n\nCustomer partnership & product feedback:\n\n - Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.\n\n - Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.\n\n - In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.\n\n - Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.\n\n - Create technical documentation, integration guides and best-practice resources.\n\n - Spend time working on-site at international partner locations as needed.\n\nSelf development:\n\n - Stay on top of the latest developments in ML, model serving and cloud-native tooling.\n\n - Gain a strong working understanding of protein and cell biology.\n\n - Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.\n\n - Participate in knowledge sharing, e.g. organise and present at our internal reading group.\n\n - Attend and present at conferences.\n\n\nAPPLY\n\nWe offer strongly competitive compensation and benefits packages, including:\n\n - Private health insurance\n\n - Pension contributions\n\n - Generous leave policies (including gender neutral parental leave)\n\n - Hybrid working\n\n - Travel opportunities and more\n\nWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.\n\nWe welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.\n\n","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}},{"id":"850b1cdd-8d3f-46eb-a858-eeca63ccb18f","title":"Member of Technical Staff, Applied AI","department":"AI Integration","team":"AI Integration","employmentType":"FullTime","location":"San Francisco","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-02-20T18:47:04.939+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/latentlabs/850b1cdd-8d3f-46eb-a858-eeca63ccb18f","applyUrl":"https://jobs.ashbyhq.com/latentlabs/850b1cdd-8d3f-46eb-a858-eeca63ccb18f/application","descriptionHtml":"Member of Technical Staff, Applied AI
We are looking for a Member of Technical Staff with deep expertise in generative modelling to work at the interface between our frontier models and the customers who depend on them. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will develop an in-depth understanding of our proprietary generative models and apply that knowledge to deploy, adapt and optimise them within customer environments - particularly in the pharmaceutical and biotech sectors.
This is a hybrid role. You will need a researcher’s depth of understanding of our models, combined with the pragmatism and communication skills to translate that understanding into production systems that deliver scientific value for our partners.
At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.
Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.
We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.
You are a strong ML researcher with experience in generative modelling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a deep understanding of generative model architectures, training dynamics and inference behaviour.
You are a skilful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.
You are customer-facing and delivery-oriented. You thrive in environments where customer success is the primary measure of your work. You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.
You are passionate about model performance. You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed. You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.
You are mission driven and curious. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment where you must context-switch between deep technical work and customer-facing engagements.
You have experience in computational biology or protein design. You have worked on ML-driven projects in biology and understand the unique data challenges, evaluation paradigms and scientific workflows of biological modelling.
You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime.
You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields, giving you an intuitive understanding of the scientific problems our customers are solving.
Develop, deploy and adapt our models for customer environments:
Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.
Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.
Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.
Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.
Ensure deployments meet customer standards for security, performance and reliability.
Customer partnership & product feedback:
Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.
Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.
In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.
Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.
Create technical documentation, integration guides and best-practice resources.
Spend time working on-site at international partner locations as needed.
Self development:
Stay on top of the latest developments in ML, model serving and cloud-native tooling.
Gain a strong working understanding of protein and cell biology.
Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
Participate in knowledge sharing, e.g. organise and present at our internal reading group.
Attend and present at conferences.
We offer strongly competitive compensation and benefits packages, including:
Private health insurance
Pension contributions
Generous leave policies (including gender neutral parental leave)
Hybrid working
Travel opportunities and more
We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
","descriptionPlain":"Member of Technical Staff, Applied AI\n\n\n\n\nTHE OPPORTUNITY\n\nWe are looking for a Member of Technical Staff with deep expertise in generative modelling to work at the interface between our frontier models and the customers who depend on them. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will develop an in-depth understanding of our proprietary generative models and apply that knowledge to deploy, adapt and optimise them within customer environments - particularly in the pharmaceutical and biotech sectors.\n\nThis is a hybrid role. You will need a researcher’s depth of understanding of our models, combined with the pragmatism and communication skills to translate that understanding into production systems that deliver scientific value for our partners.\n\n\n\n\nWHO WE ARE\n\nAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.\n\nOur team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.\n\nWe’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.\n\n\n\n\nWHO YOU ARE\n\n - You are a strong ML researcher with experience in generative modelling. You have worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a deep understanding of generative model architectures, training dynamics and inference behaviour.\n\n - You are a skilful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience building systems that serve large models via APIs and running inference on cloud hardware, parallelising data and models across accelerators.\n\n - You are customer-facing and delivery-oriented. You thrive in environments where customer success is the primary measure of your work. You can translate complex technical concepts into clear language for scientific and non-technical stakeholders alike.\n\n - You are passionate about model performance. You have an detailed understanding of how ML libraries interplay with hardware and data and love to optimise deep learning models for training and inference speed. You use this knowledge to ensure that customer deployments are performant, cost-effective and reliable.\n\n - You are mission driven and curious. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment where you must context-switch between deep technical work and customer-facing engagements.\n \n \n\n\nWHAT SETS YOU APART (PREFERRED, NOT REQUIRED)\n\n - You have experience in computational biology or protein design. You have worked on ML-driven projects in biology and understand the unique data challenges, evaluation paradigms and scientific workflows of biological modelling.\n\n - You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime.\n\n - You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields, giving you an intuitive understanding of the scientific problems our customers are solving.\n \n \n\n\nYOUR RESPONSIBILITIES\n\nDevelop, deploy and adapt our models for customer environments:\n\n - Develop a deep working understanding of our generative models - their architectures, training data, capabilities and limitations.\n\n - Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.\n\n - Drive the end-to-end technical deployment of Latent Labs models into customer environments, designing production-grade API integrations and model-serving infrastructure.\n\n - Adapt and fine-tune models to meet specific customer requirements, collaborating closely with our research team to ensure scientific rigour.\n\n - Build ML data pipelines for customer-specific inference, evaluation and feedback workflows.\n\n - Ensure deployments meet customer standards for security, performance and reliability.\n \n \n\nCustomer partnership & product feedback:\n\n - Work embedded with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.\n\n - Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.\n\n - In collaboration with customer biology teams, plan and carry out model inference against biological targets. Quickly learn from results and feed insights back to our models.\n\n - Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.\n\n - Create technical documentation, integration guides and best-practice resources.\n\n - Spend time working on-site at international partner locations as needed.\n \n \n\nSelf development:\n\n - Stay on top of the latest developments in ML, model serving and cloud-native tooling.\n\n - Gain a strong working understanding of protein and cell biology.\n\n - Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.\n\n - Participate in knowledge sharing, e.g. organise and present at our internal reading group.\n\n - Attend and present at conferences.\n \n \n\n\nAPPLY\n\nWe offer strongly competitive compensation and benefits packages, including:\n\n - Private health insurance\n\n - Pension contributions\n\n - Generous leave policies (including gender neutral parental leave)\n\n - Hybrid working\n\n - Travel opportunities and more\n\nWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.\n\nWe welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.\n\n","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}},{"id":"8dc5159a-d6fc-4fe2-8731-84c6f0f3f559","title":"Forward Deployed AI Engineer ","department":"AI Integration","team":"AI Integration","employmentType":"FullTime","location":"London","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-02-20T18:51:55.576+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"United Kingdom","addressCountry":"United Kingdom","addressLocality":"London"}},"jobUrl":"https://jobs.ashbyhq.com/latentlabs/8dc5159a-d6fc-4fe2-8731-84c6f0f3f559","applyUrl":"https://jobs.ashbyhq.com/latentlabs/8dc5159a-d6fc-4fe2-8731-84c6f0f3f559/application","descriptionHtml":"Forward Deployed AI Engineer
We are looking for a Forward Deployed AI Engineer to serve as the critical bridge between Latent Labs’ frontier generative models and the customers who rely on them. You will work directly with pharmaceutical and biotech customers to deploy, integrate and optimise our technology within their scientific workflows. This is a highly technical, customer-facing role that combines deep infrastructure expertise with a passion for solving real-world problems in drug discovery and protein engineering.
You will work closely with our customers, understanding their unique technical environments and ensuring that our generative biology platform integrates seamlessly with their systems. You will own the full lifecycle of customer deployments - from initial technical scoping through to production-grade delivery - and act as the voice of the customer back into our product and research teams.
At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.
Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.
We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.
You have a strong CS or ML educational background. You hold a degree (BSc, MSc or PhD) in Computer Science, Machine Learning, or a closely related quantitative field. You have a solid grounding in software engineering principles and modern ML frameworks.
You have built systems that access large models via APIs. You have significant experience designing, deploying and maintaining infrastructure for large-scale model serving and have hands-on experience building robust API layers around ML models.
You are customer-facing and delivery-oriented. You have direct experience deploying AI systems for external customers. You can translate complex technical concepts into clear language for non-technical stakeholders and thrive in environments where customer success is the primary measure of your work.
You are fluent in cloud infrastructure. You have hands-on experience with AWS and ideally other major cloud platforms (GCP, Azure). You are comfortable with containerisation (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures.
You are a strong communicator and collaborator. You work effectively across functions - with research scientists and business executives alike. You are comfortable leading technical discussions, writing clear documentation, and presenting solutions to senior stakeholders at partner organisations.
You are mission driven and adaptable. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You thrive in a dynamic, fast-paced environment where priorities can shift and you need to context-switch between multiple customer engagements.
You have experience with bio or protein design models. You have worked on ML-driven projects in computational biology, protein design, or related life science domains. You understand the unique data challenges and evaluation paradigms of biological modelling.
You have contributed to generative modelling innovation. You have a track record of novel contributions to generative modelling - whether through publications, open-source work, or impactful product features.
You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime. You understand the difference between a prototype and a production system.
You have pharma or biotech industry experience. You understand the regulatory landscape, data governance requirements and scientific workflows common in pharmaceutical and biotech organisations.
Customer deployment & integration:
Drive the end-to-end technical deployment of Latent Labs models into customer environments, ensuring seamless integration with existing scientific and IT infrastructure.
Design and build production-grade API integrations, data pipelines and model-serving infrastructure tailored to each customer’s requirements.
Work on-site or embedded with pharma and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.
Ensure deployments meet enterprise standards for security, performance and reliability.
Customer advocacy & product feedback:
Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams, including spending time working on-site at international partner locations as needed
Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.
Collaborate with internal teams to shape the product roadmap based on real-world deployment learnings.
Create technical documentation, integration guides and best-practice resources for customers.
Self development:
Stay on top of the latest developments in ML infrastructure, model serving and cloud-native tooling.
Gain a strong working understanding of protein and cell biology as it relates to our product.
Participate in knowledge sharing, e.g. organise and present at our internal reading group.
We offer strongly competitive compensation and benefits packages, including:
Private health insurance
Pension contributions
Generous leave policies (including gender neutral parental leave)
Hybrid working
Travel opportunities and more
We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
","descriptionPlain":"Forward Deployed AI Engineer\n\n\nTHE OPPORTUNITY\n\nWe are looking for a Forward Deployed AI Engineer to serve as the critical bridge between Latent Labs’ frontier generative models and the customers who rely on them. You will work directly with pharmaceutical and biotech customers to deploy, integrate and optimise our technology within their scientific workflows. This is a highly technical, customer-facing role that combines deep infrastructure expertise with a passion for solving real-world problems in drug discovery and protein engineering.\n\nYou will work closely with our customers, understanding their unique technical environments and ensuring that our generative biology platform integrates seamlessly with their systems. You will own the full lifecycle of customer deployments - from initial technical scoping through to production-grade delivery - and act as the voice of the customer back into our product and research teams.\n\n\nWHO WE ARE\n\nAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.\n\nOur team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.\n\nWe’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.\n\n\nWHO YOU ARE\n\n - You have a strong CS or ML educational background. You hold a degree (BSc, MSc or PhD) in Computer Science, Machine Learning, or a closely related quantitative field. You have a solid grounding in software engineering principles and modern ML frameworks.\n\n - You have built systems that access large models via APIs. You have significant experience designing, deploying and maintaining infrastructure for large-scale model serving and have hands-on experience building robust API layers around ML models.\n\n - You are customer-facing and delivery-oriented. You have direct experience deploying AI systems for external customers. You can translate complex technical concepts into clear language for non-technical stakeholders and thrive in environments where customer success is the primary measure of your work.\n\n - You are fluent in cloud infrastructure. You have hands-on experience with AWS and ideally other major cloud platforms (GCP, Azure). You are comfortable with containerisation (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures.\n\n - You are a strong communicator and collaborator. You work effectively across functions - with research scientists and business executives alike. You are comfortable leading technical discussions, writing clear documentation, and presenting solutions to senior stakeholders at partner organisations.\n\n - You are mission driven and adaptable. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You thrive in a dynamic, fast-paced environment where priorities can shift and you need to context-switch between multiple customer engagements.\n\n\nWHAT SETS YOU APART\n\n - You have experience with bio or protein design models. You have worked on ML-driven projects in computational biology, protein design, or related life science domains. You understand the unique data challenges and evaluation paradigms of biological modelling.\n\n - You have contributed to generative modelling innovation. You have a track record of novel contributions to generative modelling - whether through publications, open-source work, or impactful product features.\n\n - You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime. You understand the difference between a prototype and a production system.\n\n - You have pharma or biotech industry experience. You understand the regulatory landscape, data governance requirements and scientific workflows common in pharmaceutical and biotech organisations.\n\n\nYOUR RESPONSIBILITIES\n\nCustomer deployment & integration:\n\n - Drive the end-to-end technical deployment of Latent Labs models into customer environments, ensuring seamless integration with existing scientific and IT infrastructure.\n\n - Design and build production-grade API integrations, data pipelines and model-serving infrastructure tailored to each customer’s requirements.\n\n - Work on-site or embedded with pharma and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.\n\n - Ensure deployments meet enterprise standards for security, performance and reliability.\n\nCustomer advocacy & product feedback:\n\n - Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams, including spending time working on-site at international partner locations as needed\n\n - Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.\n\n - Collaborate with internal teams to shape the product roadmap based on real-world deployment learnings.\n\n - Create technical documentation, integration guides and best-practice resources for customers.\n\nSelf development:\n\n - Stay on top of the latest developments in ML infrastructure, model serving and cloud-native tooling.\n\n - Gain a strong working understanding of protein and cell biology as it relates to our product.\n\n - Participate in knowledge sharing, e.g. organise and present at our internal reading group.\n\n\nAPPLY\n\nWe offer strongly competitive compensation and benefits packages, including:\n\n - Private health insurance\n\n - Pension contributions\n\n - Generous leave policies (including gender neutral parental leave)\n\n - Hybrid working\n\n - Travel opportunities and more\n\nWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.\n\nWe welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.\n\n","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}},{"id":"bbb7dcf7-2311-4103-bebf-96901ca18775","title":"Forward Deployed AI Engineer ","department":"AI Integration","team":"AI Integration","employmentType":"FullTime","location":"San Francisco","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-04-08T14:22:43.203+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/latentlabs/bbb7dcf7-2311-4103-bebf-96901ca18775","applyUrl":"https://jobs.ashbyhq.com/latentlabs/bbb7dcf7-2311-4103-bebf-96901ca18775/application","descriptionHtml":"Forward Deployed AI Engineer
We are looking for a Forward Deployed AI Engineer to serve as the critical bridge between Latent Labs’ frontier generative models and the customers who rely on them. You will work directly with pharmaceutical and biotech customers to deploy, integrate and optimise our technology within their scientific workflows. This is a highly technical, customer-facing role that combines deep infrastructure expertise with a passion for solving real-world problems in drug discovery and protein engineering.
You will work closely with our customers, understanding their unique technical environments and ensuring that our generative biology platform integrates seamlessly with their systems. You will own the full lifecycle of customer deployments - from initial technical scoping through to production-grade delivery - and act as the voice of the customer back into our product and research teams.
At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.
Our team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.
We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.
You have a strong CS or ML educational background. You hold a degree (BSc, MSc or PhD) in Computer Science, Machine Learning, or a closely related quantitative field. You have a solid grounding in software engineering principles and modern ML frameworks.
You have built systems that access large models via APIs. You have significant experience designing, deploying and maintaining infrastructure for large-scale model serving and have hands-on experience building robust API layers around ML models.
You are customer-facing and delivery-oriented. You have direct experience deploying AI systems for external customers. You can translate complex technical concepts into clear language for non-technical stakeholders and thrive in environments where customer success is the primary measure of your work.
You are fluent in cloud infrastructure. You have hands-on experience with AWS and ideally other major cloud platforms (GCP, Azure). You are comfortable with containerisation (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures.
You are a strong communicator and collaborator. You work effectively across functions - with research scientists and business executives alike. You are comfortable leading technical discussions, writing clear documentation, and presenting solutions to senior stakeholders at partner organisations.
You are mission driven and adaptable. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You thrive in a dynamic, fast-paced environment where priorities can shift and you need to context-switch between multiple customer engagements.
You have experience with bio or protein design models. You have worked on ML-driven projects in computational biology, protein design, or related life science domains. You understand the unique data challenges and evaluation paradigms of biological modelling.
You have contributed to generative modelling innovation. You have a track record of novel contributions to generative modelling - whether through publications, open-source work, or impactful product features.
You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime. You understand the difference between a prototype and a production system.
You have pharma or biotech industry experience. You understand the regulatory landscape, data governance requirements and scientific workflows common in pharmaceutical and biotech organisations.
Customer deployment & integration:
Drive the end-to-end technical deployment of Latent Labs models into customer environments, ensuring seamless integration with existing scientific and IT infrastructure.
Design and build production-grade API integrations, data pipelines and model-serving infrastructure tailored to each customer’s requirements.
Work on-site or embedded with pharma and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.
Ensure deployments meet enterprise standards for security, performance and reliability.
Customer advocacy & product feedback:
Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams, including spending time working on-site at international partner locations as needed
Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.
Collaborate with internal teams to shape the product roadmap based on real-world deployment learnings.
Create technical documentation, integration guides and best-practice resources for customers.
Self development:
Stay on top of the latest developments in ML infrastructure, model serving and cloud-native tooling.
Gain a strong working understanding of protein and cell biology as it relates to our product.
Participate in knowledge sharing, e.g. organise and present at our internal reading group.
We offer strongly competitive compensation and benefits packages, including:
Private health insurance
Pension contributions
Generous leave policies (including gender neutral parental leave)
Hybrid working
Travel opportunities and more
We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
","descriptionPlain":"Forward Deployed AI Engineer\n\n\nTHE OPPORTUNITY\n\nWe are looking for a Forward Deployed AI Engineer to serve as the critical bridge between Latent Labs’ frontier generative models and the customers who rely on them. You will work directly with pharmaceutical and biotech customers to deploy, integrate and optimise our technology within their scientific workflows. This is a highly technical, customer-facing role that combines deep infrastructure expertise with a passion for solving real-world problems in drug discovery and protein engineering.\n\nYou will work closely with our customers, understanding their unique technical environments and ensuring that our generative biology platform integrates seamlessly with their systems. You will own the full lifecycle of customer deployments - from initial technical scoping through to production-grade delivery - and act as the voice of the customer back into our product and research teams.\n\n\nWHO WE ARE\n\nAt Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.\n\nOur team is committed to interdisciplinary exchange, continuous learning and collaboration. Team offsites help us foster a culture of trust across our London and San Francisco sites.\n\nWe’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact. Join us on our moonshot mission.\n\n\nWHO YOU ARE\n\n - You have a strong CS or ML educational background. You hold a degree (BSc, MSc or PhD) in Computer Science, Machine Learning, or a closely related quantitative field. You have a solid grounding in software engineering principles and modern ML frameworks.\n\n - You have built systems that access large models via APIs. You have significant experience designing, deploying and maintaining infrastructure for large-scale model serving and have hands-on experience building robust API layers around ML models.\n\n - You are customer-facing and delivery-oriented. You have direct experience deploying AI systems for external customers. You can translate complex technical concepts into clear language for non-technical stakeholders and thrive in environments where customer success is the primary measure of your work.\n\n - You are fluent in cloud infrastructure. You have hands-on experience with AWS and ideally other major cloud platforms (GCP, Azure). You are comfortable with containerisation (Docker, Kubernetes), CI/CD pipelines, and cloud-native architectures.\n\n - You are a strong communicator and collaborator. You work effectively across functions - with research scientists and business executives alike. You are comfortable leading technical discussions, writing clear documentation, and presenting solutions to senior stakeholders at partner organisations.\n\n - You are mission driven and adaptable. You are passionate about making a positive impact on the world, whether it’s for patients, customers or beyond. You thrive in a dynamic, fast-paced environment where priorities can shift and you need to context-switch between multiple customer engagements.\n\n\nWHAT SETS YOU APART\n\n - You have experience with bio or protein design models. You have worked on ML-driven projects in computational biology, protein design, or related life science domains. You understand the unique data challenges and evaluation paradigms of biological modelling.\n\n - You have contributed to generative modelling innovation. You have a track record of novel contributions to generative modelling - whether through publications, open-source work, or impactful product features.\n\n - You have built production enterprise software. You have experience delivering software that meets enterprise-grade requirements for security, compliance, auditability and uptime. You understand the difference between a prototype and a production system.\n\n - You have pharma or biotech industry experience. You understand the regulatory landscape, data governance requirements and scientific workflows common in pharmaceutical and biotech organisations.\n\n\nYOUR RESPONSIBILITIES\n\nCustomer deployment & integration:\n\n - Drive the end-to-end technical deployment of Latent Labs models into customer environments, ensuring seamless integration with existing scientific and IT infrastructure.\n\n - Design and build production-grade API integrations, data pipelines and model-serving infrastructure tailored to each customer’s requirements.\n\n - Work on-site or embedded with pharma and biotech partners to scope technical requirements, troubleshoot issues and deliver solutions.\n\n - Ensure deployments meet enterprise standards for security, performance and reliability.\n\nCustomer advocacy & product feedback:\n\n - Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams, including spending time working on-site at international partner locations as needed\n\n - Gather and synthesise customer feedback, translating it into actionable insights for our product, research and platform teams.\n\n - Collaborate with internal teams to shape the product roadmap based on real-world deployment learnings.\n\n - Create technical documentation, integration guides and best-practice resources for customers.\n\nSelf development:\n\n - Stay on top of the latest developments in ML infrastructure, model serving and cloud-native tooling.\n\n - Gain a strong working understanding of protein and cell biology as it relates to our product.\n\n - Participate in knowledge sharing, e.g. organise and present at our internal reading group.\n\n\nAPPLY\n\nWe offer strongly competitive compensation and benefits packages, including:\n\n - Private health insurance\n\n - Pension contributions\n\n - Generous leave policies (including gender neutral parental leave)\n\n - Hybrid working\n\n - Travel opportunities and more\n\nWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.\n\nWe welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.\n\n","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}},{"id":"110a5e8d-bb5b-4148-a398-97f025feb53b","title":"Machine Learning Scientist ","department":"Foundation Models","team":"Foundation Models","employmentType":"FullTime","location":"London","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-06-29T14:43:21.223+00:00","isListed":true,"isRemote":true,"workplaceType":"Hybrid","address":{"postalAddress":{"addressRegion":"United Kingdom","addressCountry":"United Kingdom","addressLocality":"London"}},"jobUrl":"https://jobs.ashbyhq.com/latentlabs/110a5e8d-bb5b-4148-a398-97f025feb53b","applyUrl":"https://jobs.ashbyhq.com/latentlabs/110a5e8d-bb5b-4148-a398-97f025feb53b/application","descriptionHtml":"We are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.
You are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling.
You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators.
You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale.
You are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics.
You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear.
You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.
You have experience in computational biology or protein design. You have worked on ML-driven projects in biology.
You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.
Build machine learning models that work in the physical world [~90% of your time]:
Contribute to a careful curation of our training and evaluation data.
Propose and build ML evaluation metrics that align with real world success and company goals.
Quickly prototype generative models against our lead metrics and perform deep analyses of improvements.
Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
Contribute to the maintenance of our compute and ML development infrastructure.
In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.
Quickly learn from wet lab results and feedback data to our models.
Self development [~10% of your time]:
Stay on top of the latest developments in ML.
Gain a strong working understanding of protein and cell biology.
Participate in knowledge sharing, e.g. organize and present at our internal reading group.
Attend and present at conferences.
We offer strongly competitive compensation and benefits packages, including:
Private health insurance
Pension/401(K) contributions
Generous leave policies (including gender neutral parental leave)
Hybrid working
Travel opportunities and more
We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
","descriptionPlain":"THE OPPORTUNITY\n\nWe are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.\n\n\n\n\nWHO YOU ARE\n\n - You are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling.\n\n - You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators.\n\n - You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale.\n\n - You are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics.\n\n - You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear.\n You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.\n\n\n\n\nWHAT SETS YOU APART\n\n - You have experience in computational biology or protein design. You have worked on ML-driven projects in biology.\n\n - You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.\n\n\n\n\nYOUR RESPONSIBILITIES\n\n - Build machine learning models that work in the physical world [~90% of your time]:\n \n - Contribute to a careful curation of our training and evaluation data.\n \n - Propose and build ML evaluation metrics that align with real world success and company goals.\n \n - Quickly prototype generative models against our lead metrics and perform deep analyses of improvements.\n \n - Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.\n \n - Contribute to the maintenance of our compute and ML development infrastructure.\n \n - In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.\n \n - Quickly learn from wet lab results and feedback data to our models.\n\n - Self development [~10% of your time]:\n \n - Stay on top of the latest developments in ML.\n \n - Gain a strong working understanding of protein and cell biology.\n \n - Participate in knowledge sharing, e.g. organize and present at our internal reading group.\n \n - Attend and present at conferences.\n\n\n\n\nAPPLY\n\nWe offer strongly competitive compensation and benefits packages, including:\n\n - Private health insurance\n\n - Pension/401(K) contributions\n\n - Generous leave policies (including gender neutral parental leave)\n\n - Hybrid working\n\n - Travel opportunities and more\n\n\n\nWe also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.\n\n\n\nWe welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.","compensation":{"compensationTierSummary":null,"scrapeableCompensationSalarySummary":null,"compensationTiers":[],"summaryComponents":[]}}],"apiVersion":"1"}