Your Impact at Lila
As an Operations Research Scientist at Lila, you will develop algorithms to orchestrate the autonomous laboratories that serve as the intelligent physical infrastructure of our scientific superintelligence platform. You’ll design logic to translate scientific priorities into schedulable, dispatchable plans for autonomous systems that adapt dynamically to real-time execution constraints. You’ll work collaboratively to deploy production software implementing these solutions. Your work will accelerate our mission by enabling fully autonomous workflows for scientific discovery, combining cutting-edge robotics, machine learning, and systems engineering.
What You'll Be Building
- Formulate and solve large-scale, inter-connected optimization problems for task allocation, scheduling, and dynamic routing under uncertainty within high-throughput automated laboratories
- Design custom heuristics and meta-heuristics to handle NP-hard challenges in real-time
- Building and using simulations to model diverse lab scenarios, benchmark approaches, and identify bottlenecks before deployment
- Collaborate with the robotics and software teams to implement optimization models into real-world autonomous systems
What You’ll Need To Succeed
- Ph.D. or M.S. in Operations Research, Computer Science, Applied Mathematics, Industrial Engineering, a related field, or equivalent experience
- Deep expertise in discrete optimization, for example in mixed-integer programming (MIP), constraint programming (CP), network flow, etc.
- Ability to model complex temporal constraints and dependencies in dynamic environments
- Ability to work and communicate cross-functionally on projects with evolving scope
- Strong software development skills, with experience deploying optimization logic into production environments
- Familiarity using a variety of commercial or open-source MILP/CP/hueristic solvers (e.g., Gurobi, CPLEX, Google OR-Tools, Hexaly, cuOpt etc..)
Bonus Points For
- Background in stochastic optimization or decision-making under uncertainty
- Experience integrating optimization logic into robot control stacks or automated laboratories
- Familiarity with temporal constraint networks
- Experience developing solvers or benchmarking algorithms
- Strong publication record in optimization algorithms
About Lila
Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at www.lila.ai
If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply.
Compensation
We expect the base salary for this role to fall between
$176,000–$304,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.
We’re All In
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.
Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
