Senior DevOps Engineer

Rhoda Ai

Job details

  • UNKNOWN
  • FULL_TIME
  • Mountain View
  • United States
  • Verified 2026-09-25
  • Salary: USD 175,000–250,000/yr
  • Source: Rhoda Ai public ASHBY source

Original job description

At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.

Responsibility:

  • Maintain and improve our CI/CD pipeline: instrument and monitor our CI jobs, and iteratively improve on it.

  • Manage and maintain infrastructure around build artifacts and dependencies storage.

  • Build and improve on our cloud and GPU cluster, and create essential devops infrastructure to support our daily research and software development effort.

  • Improve our MLOps training and deployment path: checkpoint registry/DB, model artifact promotion, and rollout to inference/robot endpoints.

  • Improve our infrastructure observability.

  • Harden security & multi-tenancy

Qualifications

  • 5+ years in DevOps / SRE / platform / infra, with ownership of production systems.

  • Proficient in a programming language such as Python, C++, Rust, Go

  • Strong knowledge of software engineering best practices and design patterns

  • Experience with docker and containerized environments

  • Experience with software build systems for cloud infrastructure and embedded systems.

  • Experience with procedural CI and CD, and build artifact delivery (OTA update) system.

  • Comfortable with operating in Linux environment

  • Self-starter mentality — comfortable with ambiguity, able to prioritize independently, and willing to jump in wherever needed

  • Effective communication skills; able to work cross-functionally in a fast-moving team

Preferred Qualifications

  • Knowledge of industrial communication protocols (EtherCAT, Modbus, gRPC, etc.)

  • Experience with ML Ops

  • Understanding of networking fundamentals (TCP/IP, DNS, firewalls) and security best practices for embedded IoT devices

  • Knowledge with kubernetes and cloud system orchestration

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