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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Hardware Systems Engineer - **Company:** Crusoe's Inc - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $215,000.0 - $260,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Computing Platforms, Systems Engineering, Automation of Tests, Cloud Computing, Configuration Management, Profiling, Computer Programming, Computer Networks, Computer Engineering, System Configuration, Software Debugging, Distributed Computing Environment, Firmware, Hardware Design, InfiniBand, Systems Analysis, Python (Programming Language), Unix Shell, PCI Express, Performance Tuning, Remote Direct Memory Access, Reduced Instruction Set Computing, Software Engineering, Scripting, Graphics Processing Unit (GPU), Computer Network Operations, High Performance Computing, Reliability of Systems, Information Technology, Machine Learning Operations, Multiplatform, Server Operating Systems & Platforms - **Published:** July 31, 2026 - **Apply:** https://www.careerbuilder.com/job-details/staff-hardware-systems-engineer-san-francisco-ca--85fd108e-6f52-49b9-bc80-362b2c7d8123 ## About the Role * 8+ 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., ARM (Advanced RISC Machine), Alternative Energy, Analysis Skills, Artificial Intelligence (AI), Automation, Benchmarking, Broadband, CPU (Central Processing Unit), Cloud Computing, Communication Skills, Computer Engineering, Computer Firmware, Computer Science, Computer Systems, Construction, Customer Support/Service, Data Analysis, Debugging Skills, Electrical Engineering, Energy Efficiency, GPU (Graphics Processing Unit), Hardware Configuration Management, Hardware Design, Input/Output, Manufacturing, Memory Hardware, Multiplatform/Cross-Platform, Network Operations Center, Network Software, PCI Express (PCI-E), Performance Analysis, Performance Engineering, Performance Management, Performance Reviews, Performance Tuning/Optimization, Problem Solving Skills, Process Improvement, Product/Service Launch, Production Support, Prototyping, Python Programming/Scripting Language, Return on Capital Employed (ROCE), Root Cause Analysis, Server Architecture, Software Design, Systems Administration/Management, Systems Analysis, Systems Engineering, Systems Reliability, Team Player, Telemetry, Test Automation, Topology, Total Cost of Ownership, Unix Shell Programming, Vehicle Fleets, x86 Processors ## Description We are seeking a 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. ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Playing Pong on a shoulder press machine](https://www.wearedevelopers.com/videos/100140-playing-pong-on-a-shoulder-press-machine) - [Profiling Symfony & PHP apps with Blackfire](https://www.wearedevelopers.com/videos/265-profiling-symfony-php-apps-with-blackfire) - [JavaScript? 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