At Rhoda AI, we're building the full-stack foundation for the next generation of humanoid robots — from high-performance, software-defined hardware to the foundational models and video world models that control it. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling scenarios unseen in training. We work at the intersection of large-scale learning, robotics, and systems, with a research team that includes researchers from Stanford, Berkeley, Harvard, and beyond. We're not building a feature; we're building a new computing platform for physical work — and with over $400M raised, we're investing aggressively in the R&D, hardware development, and manufacturing scale-up to make that a reality.

We're looking for a Full Stack Software Engineer to help develop our automation platform. This internal tool is critical to how we collect data, validate task performance, manage model versions, and rapidly iterate on model training and deployment.

What You'll Do

• Build interfaces for data collection, labeling, and grouping

• Implement tools to validate model performance and data quality

• Build interfaces for interaction with foundation models and integrate with our physical robot ecosystem

• Design and maintain backend services and APIs that support fast-moving research and engineering workflows

• 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

What We're Looking For

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

• Strong proficiency in a front-end framework (React, Vue, or similar)

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

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

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

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

Nice to Have (But Not Required)

• Familiarity with ML training pipelines

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

• Experience integrating with warehouse or logistics systems (e.g., WMS)

• Experience building tooling for dataset management, model versioning, or experiment tracking

Why This Role

• 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