About this role
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
Qualifications5+ 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 QualificationsKnowledge 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