Staff Accelerator Systems Engineer

RadixArk; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive compensation

Equity

Flexible work arrangements

Health benefits

Job summary

RadixArk is seeking a Member of Technical Staff in Accelerator Systems to push the performance envelope for frontier AI systems. You will bring up, optimize, and maintain SGLang, Miles, and the RadixArk infrastructure across NVIDIA and AMD GPUs, Google TPUs, modern server CPUs, and emerging accelerators, porting kernels and runtimes onto unfamiliar hardware and designing portable abstractions.

This role works directly with silicon and partners on pre-release platforms with immature tooling,

Qualifications

• 4+ years of experience in systems, performance, or ML infrastructure engineering.
• Deep expertise in at least one accelerator programming model (CUDA, ROCm/HIP, Pallas/XLA, Triton) or vendor SDK.
• Strong understanding of accelerator architecture: memory hierarchy, bandwidth limits, occupancy.
• Experience writing or optimizing high-performance kernels for ML workloads.
• Experience with distributed execution and communication libraries (NCCL, RCCL, MPI).
• Proficiency in C++ and Python.
• Strong debugging and profiling skills at the system level.
• Track record of performance work that shipped into production.

Responsibilities

• Bring up RadixArk's inference and training systems on new accelerator platforms and drive them to competitive performance.
• Design hardware abstractions that let a single codebase stay fast across vendors without forking.
• Port and optimize kernels across programming models and memory architectures.
• Build cross-platform benchmarking, profiling, and regression detection so performance claims hold up on every target.
• Debug numerical divergence and correctness gaps between platforms.
• Work with vendor engineering teams on pre-release hardware, compiler and driver issues, and roadmap feedback.
• Partner with kernel, runtime, distributed systems, and product engineers to land performance wins end to end.
• Serve as the internal source of truth on what each platform is actually good at.
• Contribute hardware-specific optimizations, benchmarks, and portability work back to open-source SGLang and Miles.

Skills

Performance engineering

ML infrastructure

C++

Python

Debugging & profiling

Large-scale distributed systems

Tools

CUDA

ROCm/HIP

Triton

NCCL

MPI

SGLang

Miles

Megatron

Job description

RadixArk is seeking a Member of Technical Staff in Accelerator Systems to push the performance envelope for frontier AI systems. You will bring up, optimize, and maintain SGLang, Miles, and the RadixArk infrastructure across NVIDIA and AMD GPUs, Google TPUs, modern server CPUs, and emerging accelerators, porting kernels and runtimes onto unfamiliar hardware and designing portable abstractions.

This role works directly with silicon and partners on pre-release platforms with immature tooling,