Latent Labs

Research Scientist

• Develop and execute high-throughput molecular biology or biochemistry workflows to characterize and validate novel protein designs
• Scope and integrate high-throughput wet- and dry-lab tools into experimental workflows
• Contribute to development and improvement of existing high-throughput screening platform
• Detailed, accurate, and timely documentation of experimental procedures and parameters and handoff of data and analysis results to stakeholders.
• Regular communications of experimental outcomes and analysis results to team members and stakeholders.
• Help document and contextualize experimental results for use by ML/AI collaborators
• Stay current with literature to inform assay design and identify best-in-class methodologies.
• Participate in cross-functional discussions to help translate wet lab findings into actionable model insights.
• Support preparation of internal scientific reports, presentations, and potential publications or patents.
• Support engagement with CROs or academic collaborators to extend screening capacity when needed.

Software Engineer

• Build machine learning models that work in the physical world
• 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.
• 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.

Technical Staff Member

• Build autonomous scientific agents that can execute complex research workflows through natural language interaction—from protein structure analysis to experimental design.
• Architect end-to-end reasoning systems that integrate our platform capabilities with intelligent decision-making, enabling users to accomplish sophisticated tasks through simple chat interfaces.
• Develop knowledge discovery pipelines that can autonomously mine scientific literature, identify undrugged disease pathways, and propose novel therapeutic targets.
• Create scientific content at scale by building agents that can design experiments, generate hypotheses, and produce research-grade articles and blog posts.
• Pioneer autonomous lab workflows by developing agents that can design complex biological systems (like protein-based logic gates) and orchestrate their validation.
• Collaborate with scientists to understand research pain points and translate them into intelligent automation solutions.
• Publish and evangelise breakthrough applications of agentic workflows in synthetic biology through articles, blog posts, and scientific demonstrations.

Member of Technical Staff – Reasoning Workflows

• Evaluate the capabilities of our proprietary generative AI models.
• Design evaluation strategies and benchmarks to continuously evaluate the performance progress of our models.
• Lead deep-dives on select biological and therapeutic applications.
• Closely collaborate with machine learners, protein designers, and biologists to ensure the technical and biological relevance of our model evaluations.
• Incorporate and automate relevant evaluation strategies into our model training workflows.
• Leverage your analytical results to guide model performance improvements.
• Participate in knowledge sharing, e.g. organize and present at our internal reading group.
• Stay on top of the latest developments in ML and gain a strong working understanding of protein and cell biology.

Member of Technical Staff, ML for Biology

• Build machine learning models that work in the physical world
• 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.
• Stay on top of the latest developments in ML.
• Participate in knowledge sharing, e.g. organize and present at our internal reading group.
• Attend and present at conferences.

AI Engineer

• 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.
• 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.
• 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.

Forward Deployed AI Engineer

Artificial Intelligence

• 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.

Member of Technical Staff, Applied AI

• 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.
• 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.

Technical Staff Member – Applied AI

Technical Program Manager

• Coordinate research roadmaps and ensure proper documentation and milestone tracking across the organisation.
• Manage cross-functional project timelines including wet lab validation programmes, ensuring alignment between ML research, biology, and engineering workstreams.
• Oversee CRO, lab vendor and collaborator relationships, holding partners accountable to deliverables, timelines, and quality standards.
• Maintain project management tools and ensure consistent capture of initiatives, decisions, and progress across all active programmes.
• Identify and escalate risks, dependencies, and blockers, working with leadership to resolve issues and keep programmes on track.
• Drive process improvements to enhance how the team plans, prioritises, and executes on its technical and scientific goals.
• Report to Senior Leadership, ensuring visibility into progress, risks and key decisions.
• As a member of the operations team, provide wider operational support where needed.

Technical Programme Manager

• 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.
• Serve as the technical point of contact for assigned customers, building trusted relationships with their scientific and engineering teams.
• 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.
• 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.