Site Reliability Engineer, Kubernetes Platform (Top Secret Clearance)
Hawthorne · USD 145,000-195,000 · 1+ years experience · Posted Sep 25, 2026
At a glance
- Experience
- 1+ years experience
- Location
- Hawthorne
- Salary
- USD 145,000-195,000 · Base salary
About the role
- As a member of the Classified IT Systems Engineering team, the Site Reliability Engineer is involved in designing scalable systems capable of supporting a growing volume of data products being generated in mass.
- Engineers build tools that enable more efficient work and help build software systems that are secure, reliable, and autonomous.
- Engineers are responsible for the life cycle of the systems they create, including development, testing, and operational support.
Responsibilities
- Develop automation to deploy and manage compute resources both on-premises and in the cloud
- Build, maintain, and scale on-premises hardware systems designed to host GPU-accelerated machine learning workloads
- Deploy and manage core infrastructure such as databases, monitoring and storage
- Closely collaborate with software engineers to create highly scalable, operable and maintainable products
- Engage in and improve the whole lifecycle of services -- from inception and design, through deployment, operation and refinement
Requirements
- Bachelor’s degree in computer science, information systems, or an engineering discipline; OR 2+ years of professional experience in software, DevOps, or site reliability engineering in lieu of a degree
- 1+ year of experience with Kubernetes
- 1+ year of experience with Linux operating systems
- Experience in Bash, Python, and/or other scripting languages
- Experience building, maintaining, and scaling on-premises and/or cloud systems
- Active Top Secret, Top Secret SCI, or DOE Level Q clearance
- Applicant must be a U.S. citizen or national, U.S. lawful permanent resident, Refugee, or Asylee, or be eligible to obtain required authorizations from the U.S. Department of State
Preferred qualifications
- Experience hosting and pushing the state of the art in inferential model benchmarks
- Experience with systems administration, site reliability engineering, or DevOps engineering
- Experience with Python and Python-based development frameworks
- Experience with virtualization and hypervisor technologies
- Experience with automatically managing dozens or hundreds of servers
- Knowledge of performance bottlenecks and performance improvement techniques
- Excellent communications skills with the ability to communicate with customers, peers, management etc. in both formal and informal situations
- Ability to quickly learn new tools and frameworks
Benefits
- Company stock or long-term cash awards
- Discretionary bonuses
- Employee Stock Purchase Plan
- Comprehensive medical, vision, and dental coverage
- 401(k) retirement plan
- Short and long-term disability insurance
- Life insurance
- Paid parental leave
- 3 weeks of paid vacation
- 10 or more paid holidays per year
Skills
- Kubernetes
- Linux
- Bash
- Python
- GPU-accelerated Machine Learning Workloads
