Accelerator Systems Engineer

RadixArk; Palo Alto (CA); On-site; USD 210,000 - 310,000; Full time

Job summary

RadixArk is seeking a Member of Technical Staff: Accelerator Systems to push the limits of frontier AI performance. You will bring up, optimize, and maintain SGLang, Miles, and the RadixArk stack across GPUs, TPUs, CPUs, and emerging accelerators, porting kernels and runtimes while crafting abstractions for a single codebase to stay fast on all platforms.

You will work directly with silicon and partners on pre-release platforms, solving memory hierarchy challenges and architecture tradeoffs

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 and bandwidth tradeoffs.
• Experience writing or optimizing high-performance kernels for ML workloads.
• Experience with distributed execution and communication libraries (NCCL, RCCL, MPI, or equivalents).
• 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

C++

Python

CUDA

Performance profiling

Distributed systems

Tools

NCCL

RCCL

MPI

MLIR

XLA

Triton

Job description

RadixArk is seeking a Member of Technical Staff: Accelerator Systems to push the limits of frontier AI performance. You will bring up, optimize, and maintain SGLang, Miles, and the RadixArk stack across GPUs, TPUs, CPUs, and emerging accelerators, porting kernels and runtimes while crafting abstractions for a single codebase to stay fast on all platforms.

You will work directly with silicon and partners on pre-release platforms, solving memory hierarchy challenges and architecture tradeoffs