About the Role

RadixArk is looking for a TPU Systems Engineer to build high-performance inference and training systems using JAX, XLA, and Pallas. You'll push model workloads to their limits on TPU hardware, working on SGLang-JAX and other critical infrastructure that enables efficient deployment of frontier models on Google's tensor processing units.

Requirements

• 3+ years experience building production ML systems utilizing JAX/Torch, XLA, or TPU-focused frameworks. 
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or equivalent industry experience
• Deep understanding of XLA internals preferred: HLO, MLIR, operator fusion, SPMD partitioning, and sharding strategies.
• Strong performance tuning instincts across compiler and runtime layers
• Experience with distributed inference systems (e.g. SGLang, vLLM) or training frameworks (e.g. Miles, Alpa, Pathways)
• Proficiency in Python with demonstrated ability to write high-performance, production-quality code
• Experience writing custom GPU/TPU/AI Accelerator kernels. Familiarity with Pallas for kernel development is strongly preferred. 

Responsibilities

• Build high-performance inference and training systems using JAX/XLA/Pallas, including SGLang-JAX
• Push large-model workloads to the limits on the newest TPU hardwares
• Optimize end-to-end latency and throughput for LLM serving on TPU infrastructure
• Design and implement SPMD strategies for efficient distributed inference and training
• Design and implement Pallas kernels for operations that require customized low level control for best performance
• Profile and optimize XLA compilation pipelines and HLO graph transformations
• Collaborate with kernel engineers and compiler teams to achieve performance wins across the stack
• Contribute to open-source projects with TPU optimization guides, benchmarks, and architectural insights

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  About RadixArk

  RadixArk is an infrastructure-first company built by engineers who've shipped production Al systems, created SGLang (20K+ GitHub stars,the fastest open LLM serving engine),and developed Miles(our large-scale RL framework).
  We're on a mission to democratize frontier-level Al infrastructure by building world-class open systems for inference and training.
  Our team has optimized kernels serving billions of tokens daily, designed distributed training systems coordinating 10,000+ GPUs, and contributed to infrastructure that powers leading Al companies and research labs.
  We're backed by well-known infrastructure investors and partner with  NVIDIA, Google,AWS,and frontier Al labs.
  Join us in building infrastructure that givees real leverage back to the Al community.

  Compensation

  We offer competitive compensation with meaningful equity, comprehensive benefits, and flexible work arrangements. Compensation depends on location, experience, and level

  Equal Opportunity

  RadixArk is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.