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Research Lab Software Developer Jobs (NOW HIRING)

Harvard University

Research Software Engineer

Boston, MA · On-site

$59/hr

Our Lab Join our team of researchers, engineers, and designers to shape a future in which humans ... Our Research We are currently looking for a Research Software Engineer who wants to contribute to ...

Harvard University

Research Software Engineer

Boston, MA · On-site

$223K/yr

Our Lab Join our team of researchers, engineers, and designers to shape a future in which humans ... Our Research We are currently looking for a Research Software Engineer who wants to contribute to ...

AI Chopping Block

$150 - $200/hr

About the Role We are seeking a Lab Software Engineer to join our interdisciplinary data and bioinformatics engineering team, working at the intersection of AI, scientific workflows and therapeutic ...

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Research Lab Software Developer information

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How much do research lab software developer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for research lab software developer in the United States is $111,845.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $130,000.00 per year, depending on experience, location, and employer.

What are popular job titles related to Research Lab Software Developer jobs?

For Research Lab Software Developer jobs, the most frequently searched job titles are:

Staff Software Engineer, Lab Software

Cambridge, MA • On-site

Lila Sciences
See more jobs at Lila Sciencesexternal

Full-time

Re-posted 19 days ago

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

What You'll Need To Succeed

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • 8+ years of engineering experience building and deploying large-scale systems in production. You must be strong in backend.
  • Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, 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 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 & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).

Apply