Latent Labs

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.

Machine Learning Engineer

• Deploy, maintain, and optimize production and research compute clusters
• Design and implement scalable and efficient ML inference solutions
• Develop dynamic / heterogeneous compute solutions for balancing research and production needs
• Contribute to productizing model APIs for external use
• Develop infrastructure observability and monitoring solutions

Forward Deployed AI Engineer

Member of Technical Staff, Applied AI

Technical Staff Member – Applied AI

Technical Programme Manager

Forward Deployed AI Engineer

Member of Technical Staff – ML Engineering