Member of Technical Staff Applied AI
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 develop expertise in generative models and deploy, adapt, and fine-tune them for customer environments. You will build model-serving APIs and ML data pipelines, support pharmaceutical and biotech partners, uphold deployment standards, communicate customer feedback, and create technical documentation.
Requirements
- Generative modeling
- Generative model architectures
- Training dynamics
- Inference
- Machine learning code development
- Testing
- Version control
- Code review
- Model serving
- API
- Cloud hardware
- Parallel computing
- Accelerator
- Deep learning optimization
- Customer communication
Responsibilities
- Develop a working understanding of generative model architectures, training data, capabilities, and limitations
- Collaborate in a shared codebase while maintaining code standards
- Drive end-to-end model deployments into customer environments
- Design production-grade API integrations and model-serving infrastructure
- Adapt and fine-tune models for customer requirements
- Build ML data pipelines for customer-specific inference, evaluation, and feedback
- Ensure deployments meet security, performance, and reliability standards
- Scope requirements, troubleshoot issues, and deliver solutions with pharmaceutical and biotech partners
- Serve as the technical point of contact for assigned customers
- Plan and carry out model inference against biological targets with customer biology teams
- Gather customer feedback and translate it into actionable insights
- Create technical documentation, integration guides, and best-practice resources
- Stay current with ML, model serving, and cloud-native tooling
- Participate in knowledge sharing and conferences
Benefits
- Private health insurance
- Pension contributions
- Generous leave policies, including gender-neutral parental leave
- Hybrid working
- Travel opportunities
