Member of Technical Staff, Applied AI
Latent Labs7 months ago
London, United KingdomSenior
Responsibilities
- Develop a deep understanding of the company’s generative models, including their architectures, training data, capabilities, and limitations.
- Collaborate with research scientists, engineers, and protein designers in a shared codebase while maintaining high code standards.
- Drive end-to-end deployment of models into customer environments, including production-grade API integrations and model-serving infrastructure.
- Adapt and fine-tune models for customer requirements in collaboration with the research team.
- Build ML data pipelines for customer-specific inference, evaluation, and feedback workflows.
- Ensure customer deployments meet security, performance, and reliability standards.
- Work with pharmaceutical and biotech partners to scope technical requirements, troubleshoot issues, and deliver solutions.
- Serve as the technical point of contact for assigned customers and build relationships with their scientific and engineering teams.
- Plan and conduct model inference against biological targets with customer biology teams, then feed insights back into the models.
- Synthesize customer feedback into actionable insights for product, research, and platform teams.
- Create technical documentation, integration guides, and best-practice resources.
- Work on-site at international partner locations as needed.
- Stay current with ML, model serving, and cloud-native tooling; develop knowledge of protein and cell biology; share knowledge internally; and attend and present at conferences.
Requirements
- Strong machine-learning research experience focused on generative modeling, demonstrated through notable projects, open-source contributions, product launches, or high-impact publications.
- Deep understanding of generative-model architectures, training dynamics, and inference behavior.
- Strong ML development skills, including robust production code, testing, maintainability, version control, and code review.
- Experience serving large models through APIs, running inference on cloud hardware, and parallelizing data and models across accelerators.
- Ability to translate complex technical concepts for scientific and non-technical stakeholders.
- Experience optimizing deep-learning models for training and inference speed, performance, cost-effectiveness, and reliability.
- Customer-facing, delivery-oriented approach with the ability to context-switch between technical work and customer engagements.
- Preferred: experience in computational biology or protein design and ML-driven biology projects.
- Preferred: experience delivering production enterprise software meeting security, compliance, auditability, and uptime requirements.
- Preferred: academic training in physics, biology, chemistry, or a related natural-science field.
Benefits
- Private health insurance
- Pension contributions
- Generous leave policies, including gender-neutral parental leave
- Hybrid working
- Travel opportunities
- Opportunity to shape the future of synthetic biology through generative models
Categories
ML EngineeringSolutions Engineering
About Latent Labs
Latent Labs builds generative AI and foundational models to make biology programmable, enabling design and optimization of proteins, antibodies, enzymes, and genetic constructs for pharma, biotech, and synthetic biology teams. It works with partners to co-develop candidates and provide model access with wet-lab validation through research collaborations and licensing. The company is privately held and raised a Series A in 2025.