Senior DevOps Engineer

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