Member of Technical Staff, Systems Infrastructure (2026 PhD New Grad)

THE ROLE

This role is designed for systems researchers finishing their PhD who want to see their ideas run on real fleets at real scale. As a Member of Technical Staff on the Systems Infrastructure team, you'll design and build the substrate underneath Fireworks — the schedulers, storage systems, and networks that keep tens of thousands of accelerators busy and inference latency low.

The problems here are the ones your dissertation probably touched: how to place compute-intensive jobs across heterogeneous hardware without stranding capacity, how to move model weights and KV cache fast enough that they never become the bottleneck, and how to keep a datacenter network saturated with collective traffic without collapsing tail latency. The difference is that here you get a production fleet as your testbed and your work ships.

You'll be paired with a senior engineer as a mentor and given a real problem from day one. Start dates are flexible around thesis defense timelines.

KEY RESPONSIBILITIES

• Design, build, and operate core infrastructure systems for large-scale training and inference

• Model and measure system behavior — build the benchmarks, traces, and simulators needed to reason about scheduling, caching, and network performance before committing to a design

• Identify bottlenecks across the stack, from kernel and driver to scheduler policy, and drive them out with data

• Turn research ideas into production systems that hold up under real workloads, real failures, and real customers

• Work closely with the research and inference teams so that infrastructure design and model design inform each other

• Contribute to the team's technical direction by tracking emerging hardware, interconnects, and systems research

MINIMUM QUALIFICATIONS

• PhD completed within the last 6 months, or expected completion by December 2026, in Computer Science, Computer Engineering, Electrical Engineering, or a similar field

• Research background in one or more of: distributed systems, operating systems, scheduling and resource management, storage systems, computer networks, computer architecture, or high-performance computing

• Depth in at least one of the three focus areas above, demonstrated through your dissertation, publications, or systems you've built

• Strong systems programming skills in C/C++, Rust, Go, or a similar language, plus working proficiency in Python

• Experience building and evaluating real systems — not only simulation — and reasoning rigorously about performance with measurements

• Ability to communicate systems design and results clearly to audiences with different backgrounds

PREFERRED QUALIFICATIONS

• First-authored publications at top-tier systems or networking venues (OSDI, SOSP, NSDI, EuroSys, SIGCOMM, ATC, FAST, ASPLOS, MLSys, SC, or similar)

• Industry internships in infrastructure, cloud, or HPC, or meaningful open-source contributions to systems projects (Kubernetes, Ray, Slurm, vLLM, NCCL, DPDK/SPDK, Ceph, or similar)

• Hands-on experience with GPU clusters, accelerator programming (CUDA, ROCm, Triton), or heterogeneous compute environments

• Experience with Kubernetes and cloud infrastructure, or with operating multi-tenant clusters in production

• Experience with performance profiling and debugging in distributed environments

• Research or engineering experience demonstrated via grants, fellowships, patents, or systems competitions