Staff Hardware Systems Engineer

Join Crusoe's Hardware Systems Engineering team as a Staff Hardware Systems Engineer. In this role, you will participate in the full hardware lifecycle, from prototype bring-up to large-scale production, while driving automation, deep issue resolution, and reliability across Crusoe Cloud's GPU- and CPU-based infrastructure. You will collaborate with hardware, software, infrastructure, and vendor engineering teams, and your work will directly impact Crusoe's ability to deploy and operate sustainable, AI-first compute systems with world-class performance and reliability.

• Participate in the full hardware lifecycle, from prototype bring-up to large-scale production, driving automation and reliability across GPU- and CPU-based infrastructure.
• Define and execute performance characterization and validation strategies for CPU, GPU, and accelerated computing platforms, conducting in-depth workload characterization studies.
• Lead complex system-level debugging across compute, memory, storage, networking, accelerators, and platform firmware, collaborating with vendors and internal engineering teams.
• Hands-on experience with system bring-up, validation, performance characterization, and root-cause analysis of complex hardware/software issues
• Excellent technical communication skills and experience collaborating with internal engineering teams, customers, and external technology partners
• Hands-on experience with large-scale GPU or accelerated computing infrastructure for AI/ML or HPC workloads
• Experience with workload benchmarking, performance profiling, and system performance optimization across hardware and software layers
• Experience working across multiple engineering disciplines, including hardware, firmware, software, networking, and infrastructure teams
• Experience developing automation, testing, diagnostics, or data-analysis frameworks using Python, Shell, or similar languages
• Strong analytical and problem-solving skills with the ability to operate effectively in ambiguous and rapidly evolving environments
• Strong understanding of modern server and accelerator architectures, including CPU, GPU, memory, storage, networking, and high-speed interconnects such as PCIe, InfiniBand, or NVLink
• Hands-on experience with distributed training and/or inference workloads at scale, including parallelism strategies and performance tuning across the hardware/software stack
• Ability to analyze system behavior using telemetry, benchmarks, profiling tools, and other quantitative data
• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience
• 8+ years of experience in hardware systems engineering, platform engineering, performance engineering, ML systems engineering, infrastructure engineering, or related areas
• Experience influencing hardware or system configuration decisions based on workload performance data (e.g: HW/SW co-design, platform tuning studies)
• Deep experience with RDMA, RoCE, CXL, NVLink or fabric-level performance analysis
• Experience with inference serving frameworks, training frameworks, or ML compiler/runtime stacks
• Familiarity with both x86 and ARM-based server platforms
• Experience building observability, diagnostics, or fleet-level performance and reliability systems
• Experience introducing new compute technologies into production cloud or large-scale datacenter environments
• Understanding of infrastructure efficiency, power, cooling, performance-per-dollar, or total cost of ownership considerations
• Background in sustainable or energy-efficient hardware design practices
• Advanced certifications or coursework in AI/HPC hardware systems