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Member of Technical Staff — Inference-Multi-Hardware

RadixArk· Member of Technical Staff
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Palo Alto, CA$200k - $400kfull-timePosted 2mo ago

About the role

RadixArk seeks a Member of Technical Staff - Inference-Multi-Hardware to push performance for frontier AI systems across diverse hardware (NVIDIA, AMD GPUs, Google TPUs, modern CPUs, and emerging accelerators). Responsibilities include porting kernels, designing portable abstractions, and working with silicon vendors on pre-release platforms to achieve cross-vendor performance without codeforks.

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

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 a vendor SDK), with demonstrated ability to pick up new ones quickly
  • Strong understanding of accelerator architecture: memory hierarchy, bandwidth limits, occupancy, and 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, including on platforms where tooling is incomplete or unreliable
  • Track record of performance work that shipped into production

Skills

Required:Experience in systems, performance, or ML infrastructure engineeringAccelerator programming modelsC++ and PythonDebugging and profiling at system levelDistributed execution/communication libraries
Last updated Aug 18, 2026. Interested? Apply on the company site.
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About RadixArk

SHIP AI FOR ALL

RadixArk is an infrastructure-first, deep-tech company building large-scale inference and training systems for the entire AI community.

AI systemsMilesSGLangbessemer-ai-infrastructure-2026inferenceinference-inflection-pointinfrastructureopen infrastructure
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