Proven experience improving performance in production systems with tight constraints (latency, memory, bandwidth, power/thermal, or cost)
Strong proficiency with at least one relevant stack/toolchain (e.g. TensorRT, CUDA, Qualcomm QNN, Triton, OpenCL) and confidence learning adjacent frameworks quickly
Comfort operating at multiple levels of abstraction — from high‑level model behaviour down to low‑level kernel/runtime execution
Strong software engineering fundamentals (debugging, profiling, testing, and maintainable code)
Clear communicator and collaborative teammate; able to align multiple stakeholders on performance trade‑offs and priorities
(Desirable) Exposure to embedded or edge deployment of ML models, including benchmarking on real devices and handling system‑level constraints
(Desirable) Experience with NVIDIA and/or Qualcomm SoCs and performance tooling