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CrusoeCrusoeSan Francisco, CA

Software Engineer II

Develops diagnostics, observability, automation, and repair tooling for Crusoe’s GPU server fleet and data centers. The role requires 2–3 years of software engineering experience, distributed systems and cloud expertise, and proficiency in Go, Python, Java, or Rust.

140k – 165k/yr
On-site2+ YOEFullstack Engineering

About the role

Responsibilities

  • Develop deep-level diagnostics and troubleshooting for hardware faults within GPU racks and high-density compute systems.
  • Build troubleshooting and automation tooling for GPU platforms, including NVIDIA A100, H200, GB200, B200, and AMD 350X/355X.
  • Develop automation and AI agents for component-level diagnosis and remediation of failed or degraded hardware.
  • Partner with data center operations to develop tooling and AI agents for managing critical environments.
  • Create post-repair validation and testing tools, including burn-in, PyTorch, and NVIDIA NCCL, to ensure system stability and performance.
  • Own deployment, monitoring, and operational support for developed tooling to maximize GPU fleet availability and performance.
  • Develop automation and operational tooling for facilities management, power, and direct liquid-cooling hardware systems.

Requirements

  • 2–3 years of software engineering experience.
  • Ability to identify problems, rapidly develop scalable solutions, and ship them.
  • Ability to support team members working on critical or complex technical initiatives.
  • Ability to set technical direction for a specific project and execute it.
  • Expertise in distributed systems, reliability, and cloud platforms, including Kubernetes, infrastructure as code, and Google Cloud.
  • Strength in at least one programming language: Go, Python, Java, or Rust.
  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration skills.
  • Ability to work independently and within a team.

Nice to Have

  • Experience with Temporal and Kubernetes.
  • Experience working directly with hardware vendors.
  • Experience with large-scale GPU fleet operations or hyperscale data center environments.

Compensation and Benefits

  • Compensation range of $140,000–$165,000 plus bonus.
  • Restricted Stock Units included in all offers.
  • Health insurance options including HDHP and PPO, vision, and dental coverage for employees and dependents.
  • Employer HSA contributions.
  • Paid parental leave.
  • Paid life insurance and short- and long-term disability coverage.
  • Teladoc access.
  • 401(k) with a 100% match up to 4% of salary.
  • Paid time off and holidays.
  • Cell phone reimbursement.
  • Tuition reimbursement.
  • Calm app subscription.
  • Legal benefits.
  • Company-paid commuter benefit of $50 per pay period.

Skills

GoPythonJavaRustKubernetesGCPInfrastructure As CodeDistributed SystemsTemporalPyTorchnvidia ncclgpu fleet operationsAI Agentsdirect liquid coolingreliability engineering
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