Member of Technical Staff — Inference-TPU

RadixArk; Palo Alto (CA); On-site; USD 200,000 - 400,000; Full time

Job summary

RadixArk is hiring a Member of Technical Staff — TPU Systems to build high-performance inference and training systems using JAX, XLA, and Pallas. You will push model workloads to the limits on TPU hardware and contribute to critical infrastructure enabling frontier models on Google's TPUs.

Responsibilities include optimizing latency, designing SPMD strategies, and developing Pallas kernels. Join a team with deep expertise in AI infrastructure and open-source excellence, including SGLang and

Qualifications

• 3+ years of production ML systems experience.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or equivalent.
• Deep understanding of XLA internals (HLO, MLIR, fusion, SPMD, sharding).
• Strong performance tuning across compiler/runtime layers.
• Experience with distributed inference systems or training frameworks.
• Proficiency in Python for high-performance, production-quality code.
• Experience writing custom GPU/TPU/AI accelerator kernels, familiarity with Pallas.

Responsibilities

• Build high-performance inference and training systems using JAX/XLA/Pallas (SGLang-JAX).
• Push large-model workloads to the limits on the latest TPU hardware.
• Optimize end-to-end latency and throughput for LLM serving on TPU infrastructure.
• Design and implement SPMD strategies for distributed inference/training.
• Design and implement Pallas kernels for low-level optimization.
• Profile and optimize XLA compilation and HLO graph transformations.
• Collaborate with kernel engineers and compiler teams for stack-wide performance gains.
• Contribute to open-source TPU optimization guides and benchmarks.

Skills

ML systems experience

Education (BS/MS)

XLA internals

Performance tuning

Distributed inference

Python proficiency

Custom kernels

Education

Bachelor's or Master's degree in CS/EE

Tools

JAX

XLA

Pallas

Miles

Alpa

Pathways

Job description

About the Role

RadixArk is looking for a Member of Technical Staff — TPU Systems 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

About RadixArk

RadixArk is an infrastructure-first company built by engineers who've shipped production AI systems, created SGLang (30K+ GitHub stars, the fastest open LLM serving engine), and developed Miles (our large-scale RL framework). Founded by AI infrastructure veterans from xAI and NVIDIA, we're on a mission to democratize frontier-level AI 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 AI companies and research labs.

Compensation

Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.

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.