Senior Fullstack 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.

• Build frontend interfaces for data collection, labeling, model validation, and experiment tracking

• Design and maintain backend services and APIs that support fast-moving research and engineering workflows across cloud, robot, and data infrastructure

• Build tooling and dashboards for observability across cloud infrastructure, distributed training jobs, and robot fleet status

• Integrate with data infrastructure systems — storage backends, pipeline orchestration, and dataset management tools

• Build interfaces and services that connect with our physical robot ecosystem — fleet management, teleoperation, and deployment tooling

• Own reliability, performance, and scalability of internal platform tooling as usage and complexity grow

• Collaborate closely with researchers, ML engineers, and robotics teams to understand needs and ship tools that accelerate their work

• 3+ years of experience in full stack development, ideally with internal tool or platform experience

• Strong proficiency in a frontend framework (React, Vue, or similar)

• Solid backend experience in one or more languages (Python, Node.js, Go, etc.)

• Experience with cloud infrastructure and storage (e.g., AWS, GCP, S3, GCS) and backend services

• Ability to design and work with APIs (REST or gRPC) and structured data pipelines

• Comfort working across codebases and systems owned by different teams — robotics, ML, and infrastructure

• Strong attention to security, privacy, and multi-tenant data isolation

• Familiarity with ML training pipelines, model versioning, or experiment tracking tools

• Exposure to robot fleet management, robotics control systems, or teleoperation

• Experience with data infrastructure tooling — dataset management, pipeline observability, or large-scale storage systems

• Familiarity with distributed systems or cloud infrastructure concepts (Kubernetes, job scheduling, cluster monitoring)

• The platform you build is the operating system for how our researchers and engineers work — your tools directly influence how fast we can iterate on model quality and robot behavior

• Rare opportunity to build internal tooling at the intersection of physical AI and large-scale robotics, with direct visibility into how foundation models get developed and deployed

• High ownership in a small team — you ll make real product decisions, not execute design specs handed down from above