Member of Technical Staff, Systems Infrastructure (2026 PhD New Grad)
Remote • San Mateo • FullTime
Posted 5d ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
Fireworks is seeking PhD graduates to join their Systems Infrastructure team. This role is designed for individuals finishing their PhD in Computer Science, Computer Engineering, Electrical Engineering, or a similar field, who are interested in applying their research to large-scale, real-world AI infrastructure. You will be responsible for designing and building the core systems that power Fireworks, including schedulers, storage systems, and networks, to ensure efficient operation of tens of thousands of accelerators and low inference latency. You will tackle complex problems such as optimizing job placement on heterogeneous hardware, high-speed data movement for model weights, and maintaining saturated datacenter networks. You will be paired with a senior engineer mentor and work on impactful projects from day one, with start dates flexible around thesis defense.
Responsibilities
- Design, build, and operate core infrastructure systems for large-scale training and inference.
- Model and measure system behavior using benchmarks, traces, and simulators to evaluate designs.
- Identify and resolve bottlenecks across the entire technology stack, from kernel to scheduler policy.
- Translate research ideas 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 mutually informative.
- Contribute to the team's technical strategy by staying abreast of emerging hardware, interconnects, and systems research.
Requirements
- PhD completed within the last 6 months or expected by December 2026 in Computer Science, Computer Engineering, Electrical Engineering, or a similar field.
- Research background in distributed systems, operating systems, scheduling and resource management, storage systems, computer networks, computer architecture, or high-performance computing.
- Demonstrated depth in at least one of the focus areas (scheduling & resource management, distributed storage & caching, datacenter networking) through dissertation, publications, or built systems.
- Strong systems programming skills in C/C++, Rust, Go, or similar, with working proficiency in Python.
- Experience building and evaluating real systems (not just simulation) and rigorously analyzing performance with measurements.
- Ability to clearly communicate systems design and results to diverse audiences.
Benefits
- Solve Hard Problems at the forefront of AI infrastructure.
- Work with bleeding-edge technology impacting AI adoption globally.
- Opportunity for ownership and impact in a fast-growing team.
- Learn from world-class engineers and AI researchers.
- Mentorship from a senior engineer.