Senior Data Project Manager

Rhoda AIMountain View, CA
$175,000 - $250,000

About The Position

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. Mission Turn approved robot data requirements into reliable, scalable programs, serving as the technical bridge between Research/Engineering and Data Operations.

Requirements

  • 5+ years leading complex technical programs across engineering/R&D and operations.
  • Strong technical literacy across hardware, software, data systems, or robotics.
  • Demonstrated ability to bring structure to ambiguous, fast-changing programs.
  • Strong cross-functional leadership and ability to drive execution without direct authority.
  • Hands-on mindset; comfortable investigating details rather than only managing schedules.

Nice To Haves

  • Robotics, autonomous vehicle, AI data, or hardware-software systems experience preferred.

Responsibilities

  • Translate data requirements into executable plans, milestones, owners, dependencies, and timelines.
  • Drive programs from pilot, scale-up, production, to delivery.
  • Coordinate across Research, Hardware, Software, Data Infra, and Operations, including vendor dependencies through the Data Operations team.
  • Own program schedule, dependencies, risks, blockers, issue tracking, and escalation.
  • Establish a clear single source of truth through dashboards, documentation, and operating cadences.
  • Build scalable processes for how Research, Engineering, and Operations work together.
  • Dive into technical and operational details when needed, including data quality issues, hardware readiness, and cross-functional bottlenecks impacting data delivery.
  • Ensure data programs are delivered on time, at the required quality, and at the required scale.
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