Staff Machine Learning Software Engineer
Core
Design and build scalable software systems, ML pipelines, and infrastructure to support foundation model research for general-purpose robots.
Role type
Staff Machine Learning Software Engineer (Infrastructure & Systems)
Builds
Scalable ML pipelines, data ingestion systems, training infrastructure, and shared tools for robotics research
Domain
Robotics, Embodied AI, Foundation Models
Deliverable
production ML models | infrastructure
Required skills
Software engineering, ML pipeline design, system architecture, debugging, software testing, large-scale data handling, researcher collaboration
Preferred skills
Distributed training, multi-node systems, foundation model training, multimodal/vision-language models, robotics/simulation data, fast-moving research environments
Technologies
Modern ML frameworks, distributed training systems, large-scale data processing tools
Responsibilities
Design scalable ML pipelines for data ingestion, training, and evaluation; Build software systems to scale ML workloads; Develop reusable interfaces between data, models, and robotics workflows; Maintain codebase health, architecture, and testing standards; Resolve performance and reliability bottlenecks; Build infrastructure supporting multiple research projects; Translate research requirements into software solutions
Seniority
Staff, hands-on IC with strategic impact