11 days 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 and automation tooling for NVIDIA A100, H200, GB200, B200 and AMD 350X/355X GPU platforms.
- Develop automation and AI agents for component-level diagnosis and remediation of failed or degraded hardware.
- Create tooling with data center operations teams for critical-environment management, facilities power, and direct liquid-cooling systems.
- Develop post-repair validation and testing tools, including burn-in, PyTorch, and NVIDIA NCCL-based tooling.
- Own deployment, monitoring, and operational support for developed tooling to maximize GPU fleet availability and performance.
Requirements
- Require 4–6 years of software engineering experience.
- Demonstrated ability to identify problems, rapidly develop scalable solutions, and ship them.
- Ability to set technical direction for a specific project and execute independently or collaboratively.
- Expertise in distributed systems, reliability, and cloud platforms including Kubernetes and GCP.
- Strength in at least one of Go, Python, Java, or Rust.
- Strong analytical, problem-solving, communication, and collaboration skills.
- Preferred experience with Temporal and Kubernetes, direct work with hardware vendors, or large-scale GPU fleet and hyperscale data center operations.
Benefits
- Competitive compensation of up to $170,000–$205,000 plus bonus and restricted stock units.
- Health, vision, and dental insurance options, including HDHP and PPO plans, plus employer HSA contributions.
- Paid parental leave, paid life insurance, and short- and long-term disability coverage.
- 401(k) with a 100% employer match on contributions up to 4% of salary.
- Generous paid time off and holiday schedule.
- Cell phone reimbursement, tuition reimbursement, Calm app subscription, MetLife Legal, Teladoc, 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.