Radixark

Member of Technical Staff — Training

Palo Alto, CA · Staff+

Sponsorship not specifiedDetected 7 hours ago

GitAWSMachine LearningLLMsResearch

About the role

You will work on large-scale distributed training infrastructure for LLMs and generative models, pushing the limits of scale, efficiency, accuracy and reliability across 10k, or 100k+ of GPUs.
This role sits at the intersection of ML, systems, and performance engineering.
Your work will directly impact how next-generation AI models are trained and scaled.

Optimize throughput, scalability, and hardware efficiency
Develop training frameworks and infrastructure tooling
Collaborate with model researchers to support frontier experiments
Build observability systems for training performance and reliability
Drive capacity planning and cluster utilization strategies
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.
We're backed by well-known infrastructure investors and partner with Nvidia, Google, AWS, and frontier AI labs.

3+ years of experience in ML systems, or large-scale training infrastructure
Experience working on training / inference correctness or other precision-related problem
Experience debugging performance and stability issues in large post-training jobs
Experience improving training or inference efficiency.
Experience training 100+ billion-parameter models
Experience with train / inference optimization for large-scale RL or other production workload.
Familiarity with training stacks (e.g. Megatron-LM, FSDP, torchtitan, etc.) and inference stack (e.g. SGLang, vLLM, etc.)
Familiarity with post-training framework (e.g. Miles, Slime, veRL, Prime-RL, AReaL, etc.)
Experience with RDMA, InfiniBand, NVLink, NCCL/RCCL, or high-speed GPU interconnects
Experience with checkpointing, fault recovery, and elastic training.

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

We're on a mission to democratize frontier-level AI infrastructure by building world-class open systems for inference and training.

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.

t 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

This listing is sourced directly from Radixark's careers page and normalized into a canonical job model.