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Latent Labs

Develops foundational AI for molecular biology

Forward Deployed AI Engineer

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • A degree (BSc, MSc, or PhD) in Computer Science, Machine Learning, or a closely related quantitative field.
  • A strong grounding in software engineering principles and modern machine learning frameworks.
  • Significant experience designing, deploying, and maintaining infrastructure for large-scale model serving, with hands-on experience building robust API layers around machine learning models.
  • Direct experience deploying AI systems for external customers, with the ability to explain complex technical concepts to non-technical stakeholders.
  • Hands-on experience with AWS; experience with other major cloud platforms such as GCP or Azure is also noted.
  • Comfort with containerisation using Docker and Kubernetes, CI/CD pipelines, and cloud-native architectures.
  • Ability to work across functions, lead technical discussions, write clear documentation, and present solutions to senior stakeholders.
  • Adaptability in a dynamic environment involving shifting priorities and multiple customer engagements.

Responsibilities

  • Drive the end-to-end technical deployment of Latent Labs models into customer environments and integrate them with existing scientific and IT infrastructure.
  • Design and build production-grade API integrations, data pipelines, and model-serving infrastructure tailored to customer requirements.
  • Work on-site or embedded with pharmaceutical 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 and build relationships with their scientific and engineering teams, including working on-site at international partner locations as needed.
  • Gather and synthesise customer feedback into actionable insights for product, research, and platform teams.
  • Collaborate with internal teams to shape the product roadmap based on deployment learnings.
  • Create technical documentation, integration guides, and best-practice resources for customers.
  • Stay current with developments in machine-learning infrastructure, model serving, and cloud-native tooling.
  • Develop a working understanding of protein and cell biology as it relates to the product.
  • Participate in knowledge sharing, including organising and presenting at the internal reading group.

Desired Qualifications

  • Experience with biological or protein-design models, including machine-learning projects in computational biology, protein design, or related life-science domains, and understanding of biological modelling data challenges and evaluation paradigms.
  • A track record of novel contributions to generative modelling through publications, open-source work, or product features.
  • Experience delivering enterprise-grade software for security, compliance, auditability, and uptime, and understanding the distinction between prototypes and production systems.
  • Pharmaceutical or biotech industry experience, including familiarity with regulatory landscapes, data governance requirements, and scientific workflows.

About the Company

Latent Labs

Develops foundational AI for molecular biology

Latent Labs builds biology-focused foundational models and generative AI tools. These models take biological data and produce design ideas, such as antibody candidates, enzyme optimizations, and genetic constructs, to guide lab experiments. The company differentiates itself by specializing in biology-specific AI and pursuing collaboration with partners rather than consumer software. Its goal is to accelerate molecular biology by giving researchers AI-assisted design and optimization capabilities.

Company size
11-50
Company stage
Series A
Total funding
$59.1M
Headquarters
London, United Kingdom
Founded
2023

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