Director / Senior Director, AI x Lab Integration

The role

You will lead the AI x Lab Integration team to develop capabilities that allow reasoning models to translate scientific intent into executable experiments. You will set the research agenda for models that understand protocols, compose experiments, and diagnose failures.

What you will do

• Lead research across protocol understanding, intent-to-protocol generation, feasibility assessment, protocol repair, failure diagnosis, and adaptation.
• Partner with scientists to turn expert demonstrations and experimental feedback into model improvements.
• Lead research in supervised fine-tuning, reinforcement learning, tool use, and learning from execution feedback.
• Establish independent evaluations for protocol skills, decisions, and workflows.
• Hire, mentor, and lead scientists and research engineers.
• Set clear ownership and maintain strong experimental standards.
• Partner with teams responsible for laboratory execution, data infrastructure, and orchestration.

Required qualifications

• PhD in Machine Learning, Computer Science, Robotics, Computational Science, or a related field, or equivalent research and leadership experience.
• A substantial track record of leading original AI research and translating it into capabilities that work beyond a benchmark.
• Demonstrated experience developing AI capabilities for automated laboratories, scientific agents, or closed-loop experimentation.
• Experience building and leading research teams, including recruiting scientists and engineers and setting priorities.
• The ability to engage deeply with experimental scientists and translate scientific objectives into research problems.
• A hands-on leadership style comfortable reviewing model behavior and guiding technical decisions.

Nice to have

• Deep technical expertise in foundation models, post-training, reinforcement learning, agent learning, or closely related methods.
• Research in procedural reasoning, program synthesis, planning, causal reasoning, or uncertainty-aware decision-making.
• Experience in methods for learning from expert demonstrations, sparse feedback, or costly real-world experiments.
• Deep domain expertise in experimental biology, chemistry, materials science, or laboratory automation.
• A record of influential publications, open-source contributions, or deployed research systems in AI or AI for Science.
• Experience growing a small research team into a program with sustained scientific and operational impact.

Benefits

• Medical, dental, and vision coverage
• Employer-paid life and disability insurance
• Flexible time off with generous company wide holidays
• Paid parental leave
• Educational assistance program
• Commuter benefits, including bike share memberships for office based employees
• Company subsidized lunch program

About the company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. The company combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science.