Lila Sciences
AI
StaffSoftwareEngineer,LabSoftware
Neural analysis suggests this role is
optimal for Lead candidates.
“Staff Software Engineer, Lab Software at Lila Sciences. Skills: backend experience, AI, scientific discovery. Build cutting-edge tools. Own backend challenges”
What You'll Achieve.
solve humankind's greatest challenges; accelerating discovery at unprecedented speed
Industry & Context.
Problem Solving; take ownership of complex backend challenges
What They're Looking For.
Must Have
backend experience, git, development workflows, user-centered design
Nice to Have
laboratory software for life sciences, material sciences, Kubernetes, containerization, infrastructure-as-code, Terraform, CloudFormation, CI/CD pipelines, GitHub Actions
What You'll Do.
Build cutting-edge tools
Own backend challenges
Design able to explain complex ideas
How You'll Work.
Team & Collaboration
Collaborate with software engineers; lab scientists; 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 Staff Software Engineers with backend experience to join our Lab Software Team (LaS), 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 Lab as Software Team (LaS) acts as the physical and virtual execution layer for Lila's AI-driven science. This connects the Lila App to AI Science Factories (AISFs), the mechanism through which experiments are dispatched to real instruments. This team owns the full stack of lab integration: orchestration of labflows, instrument integrations, bi-directional data transfer, and the UI/UX that AI scientists and operators use to interact with the lab. What You'll Be Building Design 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 Domain Background: Exposure to laboratory software for life sciences, material sciences, or related fields. Lab Automation Experience: Experience with laboratory devices, robotics, or hardware drivers. Orchestration Systems: Experience with software orchestration platforms (Airflow, Prefect, Temporal, Dagster) and design patterns Cloud strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions). 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, dent
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