Site Reliability Engineer (AI/GPU)

Location: Houston, New York, San Francisco, or Seattle, United States

Salary: $130,000–$200,000 USD per year, with possible bonus and equity

Company

Nscale provides a GPU cloud infrastructure platform for AI-native startups and global enterprises, from bare metal through platform services.

What you will do

• Build and own automation and tooling that keeps the platform running and reduces operational toil.
• Define and maintain SLOs, SLIs, dashboards, metrics, logs, and alerting for service health.
• Lead incident response, troubleshoot production issues, perform root cause analysis, and run post-incident reviews.
• Investigate and resolve performance and reliability problems across Linux, networking, and distributed services.
• Partner with Engineering, Networking, and Infrastructure teams to improve reliability across the stack.
• Improve availability, scalability, and efficiency through code and participate in the on-call rotation.

Requirements

• 3–6 years of experience in SRE, systems engineering, or software engineering, including production experience in a data center or cloud environment.
• Strong programming skills in Python, Go, or a similar language, with a focus on automation.
• Solid knowledge of Linux, networking fundamentals, and distributed systems.
• Experience troubleshooting live production issues and owning fixes through post-incident reviews.
• Fluency with monitoring and observability, including metrics, logs, dashboards, and alerting.
• Ability to work in a fast-moving environment and participate in an on-call rotation.

Nice to have

• Experience with AI or GPU workloads or high-performance computing.
• Familiarity with InfiniBand or RDMA.
• Experience with Kubernetes and virtualized or bare-metal environments.

Culture & Benefits

• Ownership, accountability, and direct involvement with production infrastructure.
• Competitive base salary with equity, reviewed every 12 months.
• Early scope and a progression plan focused on developing selected skills.
• Flexible work approach with autonomy over the working day.