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Remedy Robotics

Remote endovascular surgery robotics with AI

Dev Ops Engineer

DevOps EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • Experience operating continuous integration and continuous delivery pipelines for polyglot codebases, including troubleshooting continuous integration systems such as GitHub Actions, building non-trivial workflows, and evaluating tradeoffs between self-hosted and managed runners.
  • Strong Linux systems administration experience and proficiency with infrastructure-as-code practices.
  • Advanced Python proficiency, with the ability to contribute to C++ and TypeScript codebases as needed.
  • Experience with cloud infrastructure such as AWS or equivalent platforms.
  • Proficiency with modern developer tooling and AI-assisted coding environments such as Claude Code or Cursor as part of daily workflow.
  • Strong communication skills and a service-oriented mindset focused on improving developer productivity across engineering teams.
  • At least 5 years of experience in DevOps, platform engineering, or infrastructure engineering on complex production systems.

Responsibilities

  • Own the developer platform end-to-end for a multidisciplinary team building an autonomous surgical robot.
  • Design, build, and operate continuous integration and continuous delivery pipelines across Python core application and machine learning, C++ robot control, and TypeScript surgical user-interface codebases with distinct testing and deployment requirements.
  • Own lab compute infrastructure, including on-premises Ubuntu servers, GPU workstations, and supporting network systems.
  • Improve developer experience across the organization, including local development environments, build systems, package management, and test reliability.
  • Integrate hardware-in-the-loop testing into continuous integration workflows where appropriate to support system-level regression testing.
  • Manage and harden infrastructure security across on-premises and cloud environments.
  • Support machine learning workflows, including GPU compute pipelines, experiment tracking, and model deployment.
  • Own cloud infrastructure for training, data processing, and remote services.
  • Partner with software, machine learning, hardware, and data teams to optimize tooling, workflows, and overall development velocity.

Desired Qualifications

  • Background in robotics, embedded systems, or scientific computing, including experience working with hardware-dependent testing environments.
  • Experience with machine learning pipeline orchestration tools such as SkyPilot, Metaflow, Ray, or similar frameworks.
  • Experience operating self-hosted GitHub Actions runners at scale.
  • Familiarity with Python monorepo tooling such as uv, Poetry, or Bazel, and C++ dependency and packaging systems such as Conan or vcpkg.
  • Experience with real-time Linux systems.
  • Experience building audit-ready build systems, including signed builds, traceable artifacts, and reproducible build processes, such as in preparation for standards like IEC 62304.
  • Prior experience in medical device development or other regulated industries.
  • Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.

About the Company

Remedy Robotics

Remote endovascular surgery robotics with AI

Remedy Robotics builds the Remedy N1 System, a remotely operable endovascular surgical robotics platform. It lets specialist physicians perform minimally invasive cardiovascular and neurointerventional procedures from any location by combining proprietary robotic hardware with AI-powered software. A portable console lets remote clinicians control multiple tools (guidewires, catheters, stents) inside catheterization labs, while AI fuses imaging data from CT, MRI, and fluoroscopy for real-time navigation. The company differentiates itself by enabling true teleoperation to overcome geographic care gaps, demonstrated by the world’s first fully remote neurointerventional procedures in humans across two hospitals. Its goal is to expand access to gold-standard endovascular treatments for millions of patients who currently lack timely specialist care, by scaling deployment in hospitals and enhancing its AI capabilities.

Company size
11-50
Company stage
Series A
Total funding
$35M
Headquarters
San Francisco, CA
Founded
2020

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