Senior DevOps Engineer

Posted 10 Days Ago
Mountain View, CA, USA
In-Office
175K-250K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics
The Role
Maintain and improve CI/CD pipelines, manage build artifact storage, operate cloud and GPU clusters, enhance MLOps training/deployment and observability, and harden security and multi-tenancy for robot infrastructure.
Summary Generated by Built In

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

Skills Required

  • 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) systems.
  • Comfortable operating in a Linux environment.
  • Self-starter mentality; comfortable with ambiguity and independent prioritization.
  • Effective communication skills; able to work cross-functionally in a fast-moving team.
  • Knowledge of industrial communication protocols (EtherCAT, Modbus, gRPC, etc.).
  • Experience with MLOps.
  • Understanding of networking fundamentals (TCP/IP, DNS, firewalls) and security for embedded IoT.
  • Knowledge of Kubernetes and cloud system orchestration.
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The Company
73 Employees
Year Founded: 2024

What We Do

Rhoda AI builds robot foundation models that learn from internet-scale video to enable manipulation-capable robots to generalize in real-world industrial environments. Using a Direct Video Action architecture and its FutureVision intelligence layer, Rhoda focuses on turnkey deployments in manufacturing, logistics, and e-commerce—aiming to move robots out of controlled labs and into reliable, adaptive production settings.

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