Forward Deployed AI Engineer
Latent Labs is an active AI-for-science company building generative models and agentic workflows for programmable biology and drug design.
Funding history
About Latent Labs
Latent Labs develops the Latent Labs Platform and the Latent-X model family and Latent-Y agent to help researchers generate protein binders, antibodies, peptides, and other therapeutic molecules.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead technical deployments of models for pharmaceutical and biotech customers. You will build APIs, data pipelines, and model-serving infrastructure; scope requirements and troubleshoot issues with partners; uphold enterprise standards; gather feedback; and create customer-facing technical documentation.
Requirements
- Computer science or machine learning education
- Software engineering principles
- Modern machine learning frameworks
- Experience designing, deploying, and maintaining large-scale model-serving infrastructure
- Experience building API layers around machine learning models
- Experience deploying AI systems for external customers
- AWS experience
- Containerization with Docker and Kubernetes
- CI/CD pipelines
- Cloud-native architecture
- Technical documentation
- Customer communication
Responsibilities
- Drive end-to-end technical deployments into customer environments
- Design and build production-grade API integrations, data pipelines, and model-serving infrastructure
- Work with pharmaceutical and biotech partners to scope requirements, troubleshoot issues, and deliver solutions
- Ensure deployments meet security, performance, and reliability standards
- Serve as the technical point of contact for assigned customers
- Gather customer feedback and translate it into actionable product insights
- Shape the product roadmap using deployment learnings
- Create technical documentation, integration guides, and best-practice resources
- Stay current with ML infrastructure, model serving, and cloud-native tooling
- Participate in internal knowledge sharing
Benefits
- Private health insurance
- Pension contributions
- Generous leave policies, including gender-neutral parental leave
- Hybrid working
- Travel opportunities