Senior Software Engineer, Data

Lila Sciences Lila Sciences · AI Frontier · One Charles Park, Cambridge, MA +1 · Software

Senior Software Engineer on the Data Platform Team building and supporting data systems for an AI Science Factory. The role involves designing and building APIs, database architecture, optimizing performance, and leveraging cloud infrastructure. Collaboration with ML researchers and scientists is key.

What you'd actually do

  1. Design & Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.
  2. Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
  3. Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
  4. Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
  5. Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.

Skills

Required

  • 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.
  • 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).
  • Experience with ORMs: Experience with and web services for CRUD services (SQL Alchemy, SQLModel, FastAPI, Django).
  • Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
  • Full Stack Development: 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.
  • 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 deliver backend solutions, balancing trade-offs between scalability, performance, and maintainability.

Nice to have

  • Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
  • Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
  • Experience with laboratory devices, robotics, or hardware

What the JD emphasized

  • Hands on experience using AI coding assistants to drive productivity is required.

Other signals

  • AI Science Factory
  • AI-driven applications
  • data backbone of Scientific Superintelligence