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About the Role

LSAI is building the computational platform that powers Lila's work in the life sciences. This role is part of the LSAI leadership team and reports to the SVP of Generative Biology. The role combines deep hands-on individual contributor work with growing management responsibility, focusing on architecting and building the core platform while also building and leading a team.

Responsibilities

• 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.

Requirements

• 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.

Skills

• Performance engineering
• Profiling
• Optimizing training and inference
• Writing or tuning CUDA or Triton kernels
• Reasoning about GPU utilization, MFU/HFU, memory bandwidth, and kernel-level bottlenecks
• Deep expertise in the modern ML systems stack
• PyTorch internals
• Mixed precision
• Distributed training across multi-GPU or multi-node clusters

Location

• U.S.

Work Type

• Full-time

Experience Level

• Leadership responsibility
• Hands-on IC work

Salary/Compensations

• $320,000—$490,000 USD

Benefits

• Competitive base compensation with bonus potential and generous early-stage equity.
• 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.
• A company subsidized lunch program.
• International benefits tailored to their region.

About the Company

• 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 system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.
• Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.

Equal Opportunity

• Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.