Senior Hardware Systems Engineer

Crusoe

$170K — $205K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-6+ years of experience in hardware systems engineering or related fields.
  • Hands-on experience with large-scale GPU or accelerated computing infrastructure.
  • Understanding of modern server architectures including CPU, GPU, and high-speed interconnects.
  • Experience with system bring-up, validation, and debugging complex issues.
  • Strong analytical skills for performance optimization across hardware and software.
  • Bachelor's or Master’s degree in a relevant engineering discipline.

Responsibilities

  • Drive the complete hardware lifecycle from prototype to production.
  • Define performance validation strategies for various compute platforms.
  • Conduct workload characterization studies to analyze compute behavior.
  • Translate insights into tuning recommendations for enhanced performance.
  • Build workload performance profiles for deploying clusters effectively.
  • Identify and resolve performance bottlenecks across systems.
  • Collaborate with vendors and teams on technology prototyping and production readiness.

Benefits

  • Industry competitive pay
  • Restricted Stock Units in a fast-growing technology company
  • Health insurance options including HDHP and PPO
  • Employer contributions to HSA accounts
  • Generous paid parental leave
  • 401(k) with 100% match up to 4%
  • Tuition reimbursement and paid time off
  • Company-paid commuter benefit of $300 per month
  • Subscription to the Calm app
  • Paid life insurance and disability coverage
Full Job Description
About This Role:

We are seeking a Senior or Staff Hardware Systems Engineer to strengthen Crusoe's Hardware Systems Engineering team and close critical skill gaps in debugging, validation, performance evaluation and production support of high-performance compute systems. 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 be collaborating with hardware, software, infrastructure, and vendor engineering teams while working across platform bring-up, validation and performance characterization. Your work will directly impact Crusoe's ability to deploy and operate sustainable, AI-first compute systems with world-class performance and reliability.

What You'll Be Working On:
  • Drive the end-to-end lifecycle of next-generation compute platforms, including evaluation, bring-up, validation, deployment, and production readiness.
  • Define and execute performance characterization and validation strategies for CPU, GPU, and accelerated computing platforms.
  • Conduct in-depth workload characterization studies across training and inference - dense, MoE, long-context, and multimodal models to understand compute, memory, communication, and I/O behavior on target platforms.
  • Translate workload and platform insights into cluster-level tuning and configuration recommendations: topology, parallelism strategy, scheduling, power, and software stack settings to maximize delivered performance and efficiency.
  • Build and maintain workload performance profiles and reference configurations that guide how clusters are deployed, tuned, and scaled for specific model families and workload classes.
  • Analyze system and workload performance, identify bottlenecks, and work across hardware and software layers to drive improvements.
  • Lead complex system-level debugging across compute, memory, storage, networking, accelerators, and platform firmware.
  • Partner with vendors and internal engineering teams on prototyping, qualification, NPI, and production readiness of new technologies.
  • Collaborate across hardware, firmware, networking, software, infrastructure, reliability, and operations teams to resolve complex platform issues.
  • Use data and system-level insights to influence platform architecture, technology selection, hardware roadmaps, and long-term infrastructure strategy.


What You'll Bring to the Team:
  • 5-6+ years of experience in hardware systems engineering, platform engineering, performance engineering, ML systems engineering, infrastructure engineering, or related areas.
  • Hands-on experience with large-scale GPU or accelerated computing infrastructure for AI/ML or HPC workloads.
  • Hands-on experience with distributed training and/or inference workloads at scale, including parallelism strategies and performance tuning across the hardware/software stack.
  • Experience with workload benchmarking, performance profiling, and system performance optimization across hardware and software layers.
  • 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 system bring-up, validation, performance characterization, and root-cause analysis of complex hardware/software issues.
  • Experience developing automation, testing, diagnostics, or data-analysis frameworks using Python, Shell, or similar languages.
  • Ability to analyze system behavior using telemetry, benchmarks, profiling tools, and other quantitative data.
  • Experience working across multiple engineering disciplines, including hardware, firmware, software, networking, and infrastructure teams.
  • Strong analytical and problem-solving skills with the ability to operate effectively in ambiguous and rapidly evolving environments.
  • Excellent technical communication skills and experience collaborating with internal engineering teams, customers, and external technology partners.
  • Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.


Bonus Points:
  • 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.


Benefits:
  • Industry competitive pay
  • Restricted Stock Units in a fast growing, well-funded technology company
  • Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents
  • Employer contributions to HSA accounts
  • Paid Parental Leave
  • Paid life insurance, short-term and long-term disability
  • Teladoc
  • 401(k) with a 100% match up to 4% of salary
  • Generous paid time off and holiday schedule
  • Cell phone reimbursement
  • Tuition reimbursement
  • Subscription to the Calm app
  • MetLife Legal
  • Company paid commuter benefit; $300 per month


Compensation Range:

Compensation will be paid in the range of $170,000 - $205,000. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data.

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