CRUSOE · San Francisco, CA

Staff Production Engineer, Compute at CRUSOE — San Francisco, CA

Full-timeSan Francisco, CAPosted 2026-07-13Apply on Ashby

Full job description

Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

About This Role:

At Crusoe Energy Systems, we are building the most sustainable, AI-first cloud infrastructure, and our Compute-focused Production Engineers are the backbone of that mission. This role is centered on supporting virtualization, hypervisor, and kernel-level performance for Crusoe’s compute infrastructure. You’ll play a vital role in deploying and optimizing bare-metal and virtualized compute platforms, ensuring performance, security, and scale for modern AI and HPC workloads.

What You'll Be Working On:

In this role, you will develop automation and observability tools to monitor Crusoe’s compute infrastructure, spanning from the kernel to orchestration layers. You will support and scale the company’s virtualization stack, including technologies such as KVM, QEMU, and other hypervisors. Collaborating with Linux kernel and hardware teams, you’ll help identify and resolve performance bottlenecks, driver issues, and optimize hardware offloads. A key focus will be on optimizing performance for AI and HPC workloads across CPU, GPU, and DPU/NIC resources. You will participate in root cause analysis for kernel crashes, hardware-software integration problems, and performance regressions, while also integrating hypervisor-level enhancements to improve guest VM reliability and workload isolation. The role involves tuning kernel subsystems such as the process scheduler, NUMA configuration, memory management, and interrupt handling. Additionally, you will work closely with platform teams to implement and validate support for emerging compute hardware, including SmartNICs, BlueField devices, and TPUs.

What You’ll Bring to the Team:

  • 8+ years of professional experience in Compute SRE, Linux system engineering, or compute infrastructure roles.
  • Strong proficiency in Linux kernel internals, with exposure to scheduler, memory allocation, and driver subsystems.
  • Experience with virtualization architectures and technologies such as KVM, Xen, QEMU, or VMware.
  • Familiarity with SmartNICs/DPUs (e.g., NVIDIA CX6/7, BlueField-3) and kernel bypass techniques.
  • Expert-level skills in at least one programming language: Go, C or Rust.
  • Experience with system-level debugging, including kdump, kexec, and kernel panic analysis.
  • Proficiency in Infrastructure as Code tooling and CI/CD practices for bare-metal or cloud infrastructure.
  • Strong understanding of compute scheduling, resource management, and high-throughput networking.

Bonus Points:

  • Experience porting or maintaining custom Linux distributions or kernels for specific platforms.
  • Exposure to AI model infrastructure and workload orchestration across GPU clusters.
  • Contributions to Linux kernel, KVM, or other low-level infrastructure projects.

Benefits

  • Competitive compensation
  • Restricted Stock Units
  • Paid time off & paid holidays
  • Comprehensive health, dental & vision insurance
  • Employer contributions to HSA account
  • Paid parental leave
  • Paid life insurance, short-term and long-term disability
  • Professional development & tuition reimbursement
  • Mental health & wellness support
  • Commuter benefits (parking & transit)
  • Cell phone stipend
  • 401(k) Retirement plan with company match up to 4% of salary
  • Volunteer time off

Compensation Range:

Compensation will be paid in the range of $209,000 – $253,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.

Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

Required skills

  • golang
  • backbone
  • continuous deployment
  • ci/cd
  • continuous integration
  • rust
  • artificial intelligence
  • linux
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Questions about this Staff Production Engineer, Compute role

Is the Staff Production Engineer, Compute role at CRUSOE still open?
Yes — this posting is active and accepting applications through 2026-08-12. Listings can close once filled, so apply soon.
Where is the Staff Production Engineer, Compute job at CRUSOE located?
This role is based in San Francisco, CA.
How do I apply for the Staff Production Engineer, Compute role at CRUSOE?
Apply directly through CRUSOE's official hiring system, or let the Jobeezy app fill out and submit the application for you automatically.
Does Jobeezy apply to jobs for me?
Yes. Jobeezy can auto-apply to roles like this Staff Production Engineer, Compute position on your behalf — you set your preferences once and confirm, and it handles the rest.

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