Open-Source/ Platform Engineer
Role details
Job location
Tech stack
Job description
The Open Source Engineer supports the research compute ecosystem powering imaging, LLM, agentic AI, and R-based analytics workloads. This role blends Linux engineering, Kubernetes administration, GPU cluster management, and open-source tooling. This is a technical, hands-on role for an individual who will support both hardware and software layers, help scale compute environments, and solve problems across a wide range of on-prem systems., * Install, configure, upgrade, and maintain on-prem Kubernetes clusters, and troubleshoot issues end-to-end.
- Serve as a Linux administrator, responsible for patching, maintaining, and troubleshooting Linux systems, including GPU nodes and compute clusters.
- Enhance and maintain Python-based image ingestion pipelines, replacing existing scripts with robust workflows that include validation and error handling.
- Install, upgrade, and maintain open-source research tools such as GitLab, Vault, Jupyter Notebooks, R/RStudio, and H2O.
- Support medical imaging infrastructure, including understanding data flows and pulling images from various on-prem and cloud sources.
- Learn and support robotics systems and lab information management systems (LIMS) for specimen intake.
- Work with high-performance computing hardware, including GPU-dense systems and networking.
- Act as a secondary support for a senior engineer, requiring the ability to learn and adapt to unfamiliar systems quickly.
Requirements
Education: A Bachelor's degree is required.
Experience: Must have strong experience in on-prem Kubernetes administration, not cloud-only. Proven experience with open-source tooling ecosystems and the ability to troubleshoot across Linux, Windows, hardware, and networking.
Technical Skills: Strong Linux administration experience. Strong Python skills for scripting and modifying code. Basic familiarity with R/RStudio and Jupyter Notebooks from a systems perspective.
Preferred Qualifications
- Experience with GPU clusters.
- Experience with DICOM or medical imaging data.
- Experience with robotics or lab automation systems.
- Experience with GitLab administration.
- Familiarity with secrets management tools like Vault.