Senior Software Engineer, Operations Research

What You'll Be Building

• Fleet orchestrator
• Scheduler
• Manufacturing Execution System
• Data pipelines
• and related software systems.

Design & Build APIs

Design and build APIs and backend services that integrate with AI-driven applications, with focus on reliability and performance.

Database Architecture & Scaling

Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.

Application Development

Drive the implementation of backend services, focusing on performance, maintainability, and reliability.

Performance & Reliability

Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.

Cloud & Infrastructure

Build and deploy production-grade systems on AWS using Kubernetes and modern DevOps practices.

Cross-Functional Collaboration

Work with robotics scientists, platform engineers, and ML teams to integrate data pipelines and orchestration into scientific workflows.

What You'll Need To Succeed

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 5–10 years of engineering experience building and deploying large-scale backend or data systems in production.
• Backend / Data Development: Experience developing distributed software and data systems (Postgres, Flyte, Temporal, NATS/MQTT, FastAPI).
• Hands-on experience using AI coding assistants to drive productivity is required.
• Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
• Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.
• Bonus Points For Experience:
• Developing scheduling software or manufacturing execution systems.
• Experience with operations research solvers (OR-Tools, HiGHS, Gurobi).
• Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• Familiarity with Python for Science: Familiarity with data science, data visualization, and ML libraries (pandas, polars, numpy, scipy, pytorch).
• Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.

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

• 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

Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region.

Expected Base Salary Range

$180,000 USD - $256,000 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 system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.