Research Software Engineer I

About the Role

The Pereira Lab at the Salk Institute for Biological Studies is seeking a Research Software Engineer I to build and maintain software that translates computer vision models into biological discovery. The lab develops SLEAP, an open-source deep learning framework for markerless pose estimation. This role is ideal for early-career individuals with research experience who enjoy coding and system building, and it can serve as a foundation for a long-term career in research software engineering.

The Research Software Engineer I will own the research software for the Institute’s plant root phenotyping program, including:

• Containerized, GPU-accelerated pipelines for processing automated scanner images.
• Deep learning pose-estimation models for extracting quantitative traits.
• Analysis-ready results delivery to collaborating laboratories.

The role spans the entire data lifecycle, from desktop acquisition software and the Bloom web application/database to open-source Python packages and deep learning models.

Key Responsibilities

• Develop, maintain, and release open-source scientific Python packages for pose-estimation-based phenotyping, utilizing professional software engineering practices like version control (Git), code review, testing, type checking, and CI/CD.
• Maintain and extend Bloom, the lab's web application and scientific database for plant phenotyping data, encompassing backend services, API, web frontend, schema design, and deployment on self-hosted infrastructure.
• Maintain and release Bloom Desktop, an Electron/React application for image acquisition on scanners and upload to Bloom, including integration with camera and data-acquisition hardware.
• Deploy and maintain self-hosted systems and services on lab servers and cloud infrastructure, including database backup/restore, object storage, and TLS certificate management.
• Build, operate, and improve containerized, GPU-accelerated analysis pipelines for processing raw imaging data through deep learning inference to quantitative trait outputs.
• Train, evaluate, and deploy deep learning pose-estimation models, and maintain the datasets, configurations, and model registries for reproducible training runs.
• Connect analysis pipelines to Bloom through data contracts, provenance tracking, and writing results back to the database.
• Run analyses on experimental datasets for collaborating laboratories and deliver documented, reproducible reports and figures.
• Support and utilize shared high-performance computing resources, including GPU cluster scheduling and containerized job workflows (e.g., Kubernetes-based schedulers, SLURM).
• Rapidly prototype, build, and iterate on internal applications, command-line tools, and utilities in response to evolving scientific needs.
• Integrate systems and services through APIs, authentication, and automation to create seamless workflows.
• Collaborate directly with biologists and scientists to understand experimental goals and translate them into technical solutions.
• Prepare and maintain documentation, runbooks, and training materials for independent researcher use.
• Contribute to the lab's open-source software community, including reviewing external contributions and responding to user issues.
• Participate in project planning and status discussions, coordinating with other Salk labs, Core facilities, and programs.
• May assist with onboarding or supervision of student trainees and interns.

Requirements & Tech Stack

• Full-stack software engineering ability.
• Proficiency in Python and at least one other language (TypeScript preferred).
• Experience building complete applications spanning back-end logic, front-end interfaces, and data storage.
• Proficiency with the scientific Python stack (e.g., NumPy, pandas, scikit-learn).
• Experience designing and querying relational databases (e.g., PostgreSQL), including schema changes and migrations.
• Working familiarity with at least one deep learning framework (e.g., PyTorch).
• Conceptual understanding of how models are trained, evaluated, and deployed.
• Demonstrated interest in computer vision and open-source software development.
• Fluency with modern, AI-assisted software development tools (e.g., Claude Code).
• Demonstrated ability to quickly learn unfamiliar systems and technologies.
• Comfort working in Linux/Unix environments with version control (Git), testing, and code review.
• A public code portfolio (e.g., GitHub) demonstrating initiative beyond coursework is strongly recommended.

Preferred Qualifications

• BS degree in computer science, engineering, quantitative science, or a related discipline.
• Master’s degree or post-baccalaureate certification in a computational or scientific field.
• Prior internship, research, or work experience in a scientific, laboratory, or academic environment.
• Full-stack web development experience with modern frameworks (e.g., React, Svelte, Vue, FastAPI, Django).
• Desktop application development, particularly with Electron or a comparable framework.
• Experience integrating software with scientific instruments or hardware.
• Experience with computer vision or image analysis, particularly on large scientific image datasets.
• Experience with containerization (e.g., Docker) and scheduling work on GPU resources (e.g., Kubernetes, SLURM).
• Experience deploying and maintaining self-hosted applications and services, including on cloud platforms (e.g., AWS, GCP).
• Experience maintaining an open-source software project.
• Academic coursework, research experience, or demonstrated interest in plant science, biology, neuroscience, or another life-science domain.
• A track record of shipping small tools or projects quickly and independently.
• Strong communication skills.

Compensation

• The expected pay range for this position is $33.00 to $38.00 an hour.

Benefits

• Salk Institute offers competitive benefits, including medical, dental, vision, retirement, paid time off, tuition reimbursement, patient advocacy services, and transit/parking program.