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RadixArk

Open-source AI infrastructure for large-scale inference

Member of Technical Staff — CI / Infrastructure - Reliability-CI Infrastructure

DevOps EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 3 years of experience operating CI/CD at scale using GitHub Actions, Buildkite, Jenkins, GitLab CI, or a similar platform.
  • Deep knowledge of Linux, Docker, and GPU computing.
  • Experience managing self-hosted runners.
  • Strong Bash and Python skills.
  • A security mindset, including understanding CI supply-chain risks, fork pull-request attack vectors, and runner hardening.
  • Experience with NVIDIA GPU drivers, CUDA, NCCL, and InfiniBand/RDMA in CI contexts.
  • Familiarity with machine-learning inference workloads, including model loading, KV cache, and quantization.

Responsibilities

  • Own CI reliability end-to-end by triaging failures, distinguishing real regressions from flaky tests and infrastructure issues, and keeping the main branch green.
  • Build regression-based CI by replacing hardcoded static thresholds with automated baseline comparison, including a metrics pipeline, durable storage, and detection logic.
  • Harden runner infrastructure with ephemeral runners, container isolation, and security hardening for fork pull-request execution.
  • Reduce CI time by right-sizing evaluation suites, deduplicating server startups, and separating pull-request smoke tests from nightly full runs.
  • Improve developer experience through faster feedback, clearer failure messages, and workflow orchestration.

Desired Qualifications

  • Experience with CI for large open-source projects with 100 or more contributors.
  • Experience with AMD ROCm or Intel XPU CI pipelines.

About the Company

RadixArk

Open-source AI infrastructure for large-scale inference

RadixArk develops large-scale AI infrastructure for training and deploying models. Its core offering is the open-source SGLang engine that accelerates model inference, complemented by Miles, an open-source framework tailored for large-scale reinforcement learning and post-training tasks. The company provides managed infrastructure and production-grade tooling for model inference and post-training, with additional commercial products built on top of its open-source foundations. Revenue comes from managed hosting services and other paid offerings. Unlike many competitors, RadixArk pursues an open-core model to keep its core technology open and accessible to researchers, startups, and enterprises while monetizing via hosted services and premium tools. The goal is to democratize frontier AI infrastructure, reducing duplicated effort and enabling the AI community to train, deploy, and operate advanced models more efficiently and affordably.

Company size
51-200
Company stage
Seed
Total funding
$100M
Headquarters
Palo Alto, CA
Founded
2025

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