Director / Senior Director, Research Engineering, Life Sciences AI

Your Impact at LILA LSAI (Life Sciences Artificial Intelligence) is building the computational platform that powers Lila's work in the life sciences. We are looking for a Research Engineer to own and build the core codebase that our models plug into, the foundation on which our scientists build and ship their work. This role is part of the LSAI leadership team and reports to the SVP of Generative Biology. This role combines deep hands-on IC work with growing management responsibility. You will personally architect and build the core platform while also building and leading a team as headcount grows. IC contribution remains the top priority for this role. What You'll Be Building Design, build, and own the foundation of the LSAI codebase, the core infrastructure that scientist-owned models plug into. Set and enforce engineering standards for code quality, testing, versioning, documentation, and repository structure. Make architectural decisions that balance rigor with the reality that most contributors are scientists first, engineers second. Anticipate infrastructure bottlenecks and define the platform roadmap to enable rapid iteration while maintaining quality and reproducibility. Build and manage an engineering team over time while remaining a primary hands-on contributor. What You'll Need to Succeed Strong track record designing and building core software platforms or frameworks that scientists and engineers depend on. Deep platform architecture expertise, with biological applications such as protein design, nucleic-acid design, or cell foundation models as a plus. Experience building infrastructure and tooling alongside scientists in a research environment without sacrificing velocity. Full ML lifecycle expertise across data, training, evaluation, and MLOps, with a track record of taking research code to production. Comfort shifting between hands-on building and strategic leadership without letting either crowd out the other. Experience mentoring people and setting technical practices across a team or organization, beyond individual output. Bonus Points For Experience in a bioML lab or scientific computing environment. Familiarity with or curiosity about computational biology, protein modeling, or ML-adjacent codebases. Comfort working around model builders, even if you do not build the models yourself. Performance engineering experience, including profiling and optimizing training and inference. Experience writing or tuning CUDA or Triton kernels. Ability to reason about GPU utilization, MFU/HFU, memory bandwidth, and kernel-level bottlenecks. Deep expertise in the modern ML systems stack, including PyTorch internals, mixed precision, and distributed training across multi-GPU or multi-node clusters. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $320,000 — $490,000 USD About LILA Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating syste…