Senior Software Engineer, Data
About The Position
Join us in shaping the future of science! We are seeking Senior 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.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- 5-8+ years of engineering experience building and deploying large-scale backend systems in production.
- Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
- Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).
- Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
- Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
- Hands on experience using AI coding assistants to drive productivity is required.
- 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.
- Proven ability to deliver backend solutions, balancing trade-offs between scalability, performance, and maintainability.
Nice To Haves
- Familiarity with Python for Science : Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
- Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
- Experience with laboratory devices, robotics, or hardware
Responsibilities
- Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.
- Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
- Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
- Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
- Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.
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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
