16 hours ago
Base Salary
$170k - $205k/yr
Responsibilities
- Develop deep-level diagnostics and troubleshooting for hardware faults in GPU racks and high-density compute systems.
- Build troubleshooting, automation, and AI-agent tooling for NVIDIA and AMD GPU platforms.
- Develop component-level diagnosis, remediation, post-repair validation, burn-in, and system stability testing tools.
- Partner with data center operations to build tooling and AI agents for critical-environment management.
- Own deployment, monitoring, and operational support for developed tooling.
- Develop automation and operational tooling for facility power and direct liquid cooling hardware systems.
- Set technical direction for projects and deliver scalable solutions that improve GPU fleet availability and performance.
Requirements
- 4–6 years of software engineering experience.
- Expertise in distributed systems, reliability, and cloud platforms, including Kubernetes, infrastructure as code, and GCP.
- Strong proficiency in at least one of Go, Python, Java, or Rust.
- Ability to identify problems, rapidly develop scalable solutions, and ship them.
- Ability to set technical direction, work independently, collaborate effectively, and support complex technical initiatives.
- Strong analytical, problem-solving, communication, and collaboration skills.
- Preferred: experience with Temporal and Kubernetes, hardware vendors, large-scale GPU fleet operations, or hyperscale data center environments.
Benefits
- Industry-competitive pay and restricted stock units.
- Health insurance options including HDHP and PPO, plus vision and dental coverage for dependents.
- Employer HSA contributions, paid parental leave, paid life insurance, and short- and long-term disability coverage.
- Teladoc, 401(k) with a 100% match up to 4% of salary, generous paid time off, and holiday schedule.
- Cell phone reimbursement, tuition reimbursement, Calm app subscription, MetLife Legal, and a company-paid commuter benefit of $50 per pay period.
About Crusoe
Crusoe builds and operates GPU-powered data centers and an AI cloud platform for enterprises running large-scale AI training and inference. It vertically integrates energy supply with compute, using stranded and renewable power to reduce emissions and costs, and sells capacity via cloud services and managed infrastructure. Founded in 2018 and headquartered in Denver, the company is privately held.