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Palo Alto, California, United States
Onsite
RadixArk is seeking a Member of Technical Staff — Training to build and scale the systems that train frontier AI models.
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.
This is a deeply technical, high-impact role for engineers who enjoy solving hard systems problems at extreme scale.
3+ years of experience in ML systems, or large-scale training infrastructure
Experience building or operating large-scale agentic post-training systems.
Experience debugging performance and stability issues in large post-training jobs
Experience training 100+ billion-parameter models
Familiarity with training stacks (e.g. Megatron-LM, FSDP, torchtitan, etc.) and inference stack (e.g. SGLang, vLLM, etc.)
Experience with RDMA, InfiniBand, NVLink, NCCL/RCCL, or high-speed GPU interconnects
Contributions to ML systems open-source projects
Experience with checkpointing, fault recovery, and elastic training.
Contribute to open-source large-scale post-training infrastructure Miles, and inference system SGLang.
Optimize throughput, scalability, and hardware efficiency
Improve reliability and fault tolerance for long-running training jobs
Develop training frameworks and infrastructure tooling
Collaborate with model researchers to support frontier experiments
Debug and resolve cross-layer performance bottlenecks
Build observability systems for training performance and reliability
Drive capacity planning and cluster utilization strategies
Contribute to long-term training infrastructure architecture
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.
Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.
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.
