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Member of Technical Staff — Training

RadixArk· Member of Technical Staff
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Palo Alto, CA$200k - $400kfull-timePosted 5mo ago

About the role

Role focused on designing, building, and operating distributed systems for large-scale model post-training, including training, inference, and orchestration across multi-GPU clusters with emphasis on performance, correctness, scalability, and reliability.

Responsibilities

  • Design, build, and operate distributed training, rollout, and orchestration systems for large-scale LLM and multimodal post-training across multi-GPU, multi-node environments.
  • Profile and optimize performance across the full-stack — model implementation, parallelism strategies, communication libraries, and GPU kernels — to improve throughput, latency, memory efficiency, hardware utilization, and cost.
  • Investigate numerical correctness and low-precision issues in distributed training and inference, including train–inference consistency for reinforcement learning.
  • Improve the reliability of long-running workloads through checkpointing, fault recovery, observability, and operational tooling.
  • Build supporting infrastructure for reinforcement learning and agentic post-training, including asynchronous rollout, trajectory collection, sandboxed execution, evaluation harnesses, and data pipelines.
  • Contribute to open-source training and inference systems, including Miles and SGLang, and partner with researchers to turn experimental requirements into production systems.

Qualifications

  • 3+ years of experience building or operating distributed machine learning systems, large-scale training infrastructure, or high-performance inference systems.
  • Hands-on experience with post-training systems, training backends, or inference systems for large language models (e.g., Megatron-LM, FSDP, SGLang, TensorRT-LLM, vLLM).
  • Experience in at least two of the following areas: performance/efficiency/scalability of multi-GPU multi-node workloads; numerical correctness or low precision; stability/reliability/fault tolerance; post-training algorithm recipes and orchestration infrastructure for large training runs; multimodal training or inference; agent infrastructure; building/maintaining open-source projects.

Skills

Required:Distributed ML systemsPost-training frameworks

Benefits

  • 401(k) plan
  • unlimited PTO
  • visa sponsorship for eligible candidates
Last updated Sep 1, 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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