Core Research Software Engineer I - Integrated Genomics Core

Staff Career•La Jolla, CA

About The Position

The Salk Institute Core Facilities support data-intensive biological research across disciplines, generating and working with large-scale datasets from genome sequencing, gene expression profiling, microscopy, spatial imaging, flow cytometry, and mass spectrometry. The Core Research Software Engineer supports day-to-day systems administration and operations for the technology infrastructure behind these facilities and their administrative services, including servers, storage, and research instruments. The role focuses on configuring, monitoring, and maintaining Core systems and user services so they remain secure, reliable, and performant. Working under the general supervision of the Director of the Integrative Genomics Core, the engineer partners with Salk Institute IT and Center for AI and Research Computing (AIRC) personnel to help Core staff implement hardware and software solutions and support complex systems. The position combines research and software engineering, working directly with scientists to translate evolving research needs into practical tools and services. The role contributes to open-source scientific software, internal applications and utilities, integrations, documentation, and training, as well as systems monitoring, operating-system maintenance, backups, storage management, and operational support. It offers the opportunity to support Salk’s scientific mission in a collaborative environment.

Requirements

A BS degree in computer science, engineering, quantitative science, or a related discipline is preferred.
Strong proficiency in Linux server administration, such as Red Hat/CentOS or Ubuntu Linux, including shell scripting and command-line tools.
Strong analytical and troubleshooting skills, including the ability to methodically isolate root causes in complex environments.
Excellent verbal and written communication skills, including the ability to document processes and explain technical issues to non-technical audiences.
A customer-service-oriented attitude when working with researchers and staff.
Ability to work independently and collaboratively, manage time effectively, and balance multiple tasks.
Full-stack software engineering ability, including proficiency in Python and at least one other programming language, and experience building applications spanning back-end logic, front-end interfaces, and data storage.
Fluency with modern AI-assisted software development, including effective use of AI coding tools and large language models to design, build, debug, and ship software.
Demonstrated ability to learn unfamiliar systems and technologies quickly and to stand up working services and pipelines through code, scripting, and automation.
Comfort working in Linux/Unix environments with version control, testing, and code review.

Nice To Haves

A 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 such as React, Svelte, Vue, FastAPI, or Django.
Experience integrating software with scientific instruments or hardware, such as cameras, scanners, or data-acquisition devices.
Experience with containerization such as Docker and scheduling work on GPU resources such as Kubernetes or SLURM; prior high-performance computing or systems-administration experience is welcome.
Experience deploying and maintaining self-hosted applications and services, including on cloud platforms such as AWS or GCP.
Experience maintaining an open-source software project, including packaging, releases, and responding to community issues.
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 and learning new languages, frameworks, and systems with minimal ramp-up.
Strong communication skills and ability to work directly with scientists to translate their needs into technical solutions.
A public code portfolio, such as GitHub, demonstrating initiative beyond coursework, including personal projects or open-source contributions.

Responsibilities

Develop, maintain, and release open-source scientific packages using professional software engineering practices, including Git, code review, testing, type checking, and CI/CD.
Support and use shared high-performance computing resources, including GPU cluster scheduling and containerized job workflows such as Kubernetes-based schedulers and SLURM.
Rapidly prototype, build, and iterate on internal applications, command-line tools, and utilities in response to scientific needs.
Integrate systems and services through APIs, authentication, and automation to create workflows for end users.
Work directly with biologists and other scientists to understand experimental goals and translate them into technical solutions.
Prepare and maintain documentation, runbooks, and training materials so researchers can use tools and pipelines independently.
Contribute to the lab’s open-source software community by reviewing external contributions and responding to user issues.
Participate in project planning and status discussions and coordinate with Salk labs, Core facilities, and programs.
Monitor Core Facilities system health and capacity and maintain service reliability and uptime.
Install and configure operating systems, primarily Linux/Unix and Windows, on servers, workstations, and other Core Facility devices; apply patches and updates.
Execute backup and restore procedures for Core Facility data, monitor on-premises and cloud backup jobs, and remediate failures.
Monitor on-premises and cloud storage usage and address routine storage, performance, and reliability issues.
Respond promptly to operational issues, document resolution steps, and record follow-up actions for team knowledge sharing.
Identify and recommend improvements to system reliability, performance, and efficiency; contribute automation and other practices to Core Facility projects and initiatives.
Perform other related duties as assigned, which may include inventory management, procedure documentation, training new team members, and cross-training in other computational areas.