Engineer II /Senior Software Engineer, Simulation

What You'll Be Building

Design and maintain a low-fidelity discrete event simulation platform modeling lab workflows, instrument states, and robotic transport.

Architect the platform so production scheduling and fleet coordination code runs with minimal changes.

Develop experiment tracking and reproducibility infrastructure so every run is logged, versioned, and comparable.

Develop tooling for parameter sweeps, scheduler benchmarks, and capacity planning across lab configurations and workloads.

Partner with Scheduling and Robotics teams to validate new scheduling and coordination strategies.

Ship clean, well-documented simulation APIs other engineers can build on.

What You'll Need To Succeed

• 1-3 years of hands-on experience in simulation engineering, operations research, or a closely related field.
• Strong software engineering fundamentals: testing, CI/CD, API design, and the ability to balance velocity with maintainability.
• Strong understanding of experiment reproducibility: seeding, versioning, logging, and structured comparison of simulation runs.
• Solid grasp of system modeling concepts: queuing, resource contention, event scheduling, and stochastic behavior.
• Strong communication skills and comfort working across teams with different technical backgrounds.

Bonus Points

• Practical experience with discrete event simulation (e.g. SimPy).
• Experience designing and maintaining internal developer tools or platforms.
• Experience in robotics, warehousing, or logistics environments where physical transport is a first-class part of the system model.
• Familiarity with scheduling algorithms or heuristics (greedy dispatching, priority rules, constraint-based approaches).
• Experience with experiment tracking platforms (MLflow, Weights & Biases, or similar).
• Comfort reasoning about the tradeoffs between simulation fidelity, speed, and coverage of production code paths.

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity.

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 system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.