Staff Engineer, Infrastructure (HPC & AI Compute)

Location: San Francisco, CA; onsite in the office five days a week

Base salary: $224,000–$284,000 per year, plus potential equity awards.

Company

hirify.global AI commercializes production-ready autonomous vehicle technology, including Autonomous Haulage Systems for mines, quarries, and construction sites.

What you will do

• Design, deploy, and commission physical GPU and HPC infrastructure for autonomous systems, AI/ML workloads, and large-scale simulation.
• Architect the foundation for thousands of GPUs, large-scale CPU compute, and Exabyte-scale storage while balancing performance, reliability, scalability, and cost.
• Evaluate GPU servers, CPUs, memory, networking, storage systems, rack configurations, and workload-specific infrastructure requirements.
• Design high-performance cluster interconnects, networking, distributed storage, and data movement systems.
• Translate compute requirements into data-center power, cooling, rack-density, space, and connectivity specifications with facilities, real estate, and infrastructure partners.
• Lead end-to-end deployment, procurement, installation, integration, validation, automation, capacity planning, incident response, and production reliability.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent practical experience.
• 8+ years of experience in infrastructure engineering, systems engineering, high-performance computing, data-center engineering, or related disciplines.
• Experience designing, deploying, commissioning, or significantly expanding physical compute infrastructure, including HPC clusters, GPU systems, or large-scale data-center environments.
• Ability to lead infrastructure initiatives from technical requirements and architecture through implementation, production readiness, and ongoing operations.
• Strong systems engineering knowledge across Linux, server hardware, networking, and storage, with deep expertise in multiple areas.
• Experience with high-performance or large-scale computing environments, including GPU/CPU clusters, distributed computing, AI/ML infrastructure, simulation, or comparable workloads.
• Hands-on infrastructure automation or tooling experience using Python, Go, Bash, C++, Ansible, or similar technologies.
• Experience evaluating hardware configurations, networking and storage technologies, vendor solutions, and performance, reliability, and cost tradeoffs.
• Knowledge of data-center requirements including power, cooling, rack density, cabling, and network connectivity; strong troubleshooting skills across hardware, operating systems, networking, and storage.
• Ability to work independently in fast-moving, ambiguous environments, collaborate across disciplines, and drive technical decisions without established processes.

Nice to have

• Experience with large-scale AI/ML training clusters, GPU supercomputers, or high-density HPC environments.
• Experience in AI infrastructure, autonomous vehicles, robotics, scientific computing, semiconductor engineering, hyperscale data centers, or GPU cloud infrastructure.
• Familiarity with NVIDIA DGX/HGX, InfiniBand, RDMA/RoCE, Slurm, Kubernetes, or other HPC and distributed-computing technologies.
• Experience with Ceph, Lustre, GPFS/Spectrum Scale, BeeGFS, or similar distributed storage systems.
• Experience with bare-metal provisioning and cluster automation using PXE, xCAT, Warewulf, NVIDIA Base Command Manager, or comparable tools.
• Exposure to modular data centers, liquid cooling, high-density racks, and large-scale power and cooling infrastructure.
• Experience working with hardware OEMs, infrastructure vendors, procurement teams, and facilities partners on capacity planning, deployments, and capital expenditure decisions.

Culture & Benefits

• Work on production-deployed autonomy that improves safety, efficiency, and productivity.
• Operate in a fast-moving environment with high ownership, complex real-world challenges, and close collaboration with experienced engineers and industry operators.
• Full-time onsite work five days per week at the San Francisco office.
• Medical, dental, vision, disability, and life insurance; FSA/HSA options; 401(k); equity; sick time; unlimited flexible time off; paid holidays; paid parental leave; and pre-tax commuter benefits.
• Team lunch at the SoMa office every Tuesday and Thursday.

Hiring process

• Applications are accepted on an ongoing basis.