Member of Technical Staff, Systems Infrastructure (2026 PhD New Grad)
$200k - $230k • Remote • San Mateo • FullTime
Posted 1mo ago
Job Location
San Mateo
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
Fireworks is seeking PhD graduates in Computer Science, Computer Engineering, or Electrical Engineering to join their Systems Infrastructure team. This role is for individuals who want to apply their research ideas to real-world, large-scale AI infrastructure. You will be responsible for designing and building the core systems that power Fireworks' AI platform, including schedulers, storage systems, and networks, ensuring efficient utilization of hardware and low inference latency. You will work on challenging problems related to compute placement, efficient data movement, and high-performance networking for AI workloads, with the opportunity to see your work ship in a production environment.
Responsibilities
- Design, build, and operate core infrastructure systems for large-scale AI training and inference.
- Model and measure system behavior using benchmarks, traces, and simulators to evaluate designs.
- Identify and resolve performance bottlenecks across the entire system stack.
- Translate research concepts into robust production systems capable of handling real-world workloads and failures.
- Collaborate with research and inference teams to ensure infrastructure and model designs are complementary.
- Contribute to the team's technical strategy by staying informed about emerging hardware and systems research.
Requirements
- PhD completed within 6 months or expected by December 2026 in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
- Research background in distributed systems, operating systems, scheduling, storage systems, computer networks, computer architecture, or high-performance computing.
- Demonstrated depth in at least one of the focus areas (scheduling, distributed storage, datacenter networking) through dissertation, publications, or built systems.
- Strong systems programming skills in C/C++, Rust, Go, or similar, with proficiency in Python.
- Experience building and evaluating real systems, not just simulations, and using measurements for performance analysis.
- Ability to clearly communicate systems design and results to diverse audiences.
Benefits
- Solve Hard Problems at the forefront of AI infrastructure.
- Build with bleeding-edge technology impacting global AI adoption.
- Ownership and Impact in a fast-growing team.
- Learn from world-class engineers and AI researchers.