Title of Role: Software Engineer (C Systems)
Location: San Francisco, CA (On-site)
Company Stage of Funding: Seed-Stage, High-Growth Venture-Backed Startup
Office Type: On-Site (5 Days/Week)
Salary: $200,000 – $250,000 base competitive equity

Company Description

Our client is a fast-growing, venture-backed infrastructure startup building cutting-edge GPU virtualization technology. Their platform powers next-generation compute workloads by enabling dramatically higher GPU utilization, efficiency, and throughput—supporting both internal GPU cloud operations and external enterprise customers.

This is an opportunity to join a deeply technical founding team that moves fast, ships aggressively, and is building software at the bleeding edge of distributed GPU systems, performance engineering, and large-scale ML infrastructure.

If you enjoy solving microsecond-level performance problems, working close to the metal, and owning highly critical systems that power real customers at scale, this role will be an exceptional fit.

What You Will Do

• Build and optimize core components of a high-performance C GPU virtualization library.

• Drive performance tuning across latency-sensitive and throughput-critical code paths.

• Conduct research into oversubscription, checkpointing, GPU sharing, and distributed GPU cluster scheduling.

• Support new GPU architectures and ensure seamless integration across the system.

• Debug complex systems-level issues in production environments.

• Diagnose performance bottlenecks in machine learning and model-training workloads.

• Collaborate closely with a senior, fast-moving engineering team to scale the platform for rapid customer growth.

Ideal Candidate Background

• Strong experience with modern C (C 17 or later), systems programming, or performance-critical backend engineering.

• Experience working on low-level systems such as hypervisors, filesystems, OS internals, networking stacks, or GPU/accelerator infrastructure.

• Skilled in debugging complex distributed systems in production environments.

• Comfortable navigating and optimizing large C codebases.

• Passion for deep systems thinking, performance engineering, and working on challenging technical problems.

• Thrives in a high-ownership, high-velocity startup environment.

Preferred Qualifications

• Experience with GPU compute, CUDA, GPU virtualization, or ML systems performance.

• Exposure to oversubscription, checkpointing, or distributed compute scheduling.

• Background in HPC, storage systems, virtualization, or cloud infrastructure.

• Experience scaling infrastructure for ML/AI workloads.

• Systems-level debugging in high-traffic, high-availability environments.

Compensation, Benefits & Additional Details

• Base Salary: $200,000 – $250,000

• Equity: Highly competitive early-stage equity package

• Work Hours: High-intensity environment; expected workload aligns with early-stage deep-tech startups

• Sponsorship: TN, Canadian visas, and H-1B transfers may be supported (no new H-1Bs)

• Relocation: Relocation assistance available for candidates moving to San Francisco

• Position Type: Full-time, on-site role with significant impact and visibility