Staff ML Engineer

Responsibilities

• Architect and build software infrastructure powering protein design and engineering pipelines, including orchestration, data flow, and APIs
• Own the engineering side of the Lab-in-the-Loop lifecycle by connecting computational outputs to experimental inputs
• Onboard new tools and methods developed by AI scientists into production-ready systems
• Partner cross-functionally with ML researchers and scientists to translate research code into scalable systems
• Set engineering standards for design reviews, CI/CD, testing, observability, and reproducibility
• Diagnose and resolve reliability, performance, and scaling bottlenecks in production pipelines

Requirements

• Master's degree or higher in Computer Science, Machine Learning, or a related quantitative field
• 8+ years of professional software engineering experience in Python
• Proven experience designing and operating scalable production systems, APIs, and data pipelines
• Strong fundamentals in system design, CI/CD, observability, and reliability
• Experience with scientific or ML-adjacent infrastructure such as workflow orchestration and experiment tracking
• Hands-on experience with containerization, orchestration platforms, and infrastructure-as-code on major cloud providers
• Track record of leading technical direction and partnering with research scientists

Preferred Qualifications

• Experience building infrastructure for protein design, antibody engineering, or molecular ML
• Familiarity with biological data formats and bioinformatics tooling
• Experience integrating ML training/inference systems with scientific platforms
• Open-source contributions to scientific computing or data infrastructure

About the Company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously.