Lila Sciences

AI Science

PrincipalSoftwareEngineer,Data

$204–348k Cambridge, Massachusetts, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Principal candidates.

The Brief

“Principal Software Engineer, Data at Lila Sciences. Skills: backend, Data Platform, AI Science. Design complex backend solutions. Explain complex ideas”

What You'll Achieve.

accelerating discovery

Industry & Context.

AI Science
Problems you'll solve

Problem Solving; design complex backend solutions

What They're Looking For.

Must Have

backend experience

Nice to Have

Kubernetes, containerization, infrastructure-as-code, Terraform, CloudFormation, CI/CD pipelines, GitHub Actions, laboratory software, analytics for life sciences, material sciences, laboratory devices, robotics, hardware

What You'll Do.

Design complex backend solutions

Explain complex ideas

How You'll Work.

Team & Collaboration

collaborate with software engineers; collaborate with lab scientists; collaborate with machine learning engineers

Communication Scope

explain complex ideas to diverse audiences

Full Job Description

Your Impact at LILA Join us in shaping the future of science! We are seeking Principal Software Engineers with backend experience to join our Data Platform Team (Data), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you! About The Team The Data Platform Team (Data) builds and support the data systems that underpins Lila's AI Science Factory™. Every experiment run in our labs, every measurement from an instrument, and every signal from our operational systems flows through the platform they build. Their work spans real-time ingestion, large-scale analytical storage, workflow orchestration, and the self-service tools scientists, engineers, and ML teams use to go from raw measurements to discoveries. They build the data backbone of Scientific Superintelligence™, so the science moves faster and each experiment makes the next one smarter. What You'll Be Building Design able to explain complex ideas to diverse audiences. Problem Solving: Proven ability to design complex backend solutions, balancing trade-offs between scalability, performance, and maintainability. Bonus Points For Cloud strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions). Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields. Experience with laboratory devices, robotics, or hardware 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. Full-time U. S. employees receive a comprehensive benefits program including medical, dental,

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