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Rhoda AI is building generalist intelligent robots with a full robotics stack spanning hardware, systems, and foundation world models. The company has raised over $450M and is scaling research, infrastructure, hardware development, and manufacturing.
You will serve as Senior Technical Program Manager for AI Research, owning integrated execution across pre-training, post-training, applied research, data, GPU infrastructure, robotic hardware, and model delivery. This is a deeply technical, cross-functional role focused on turning research complexity into predictable execution without slowing down researchers.
Key responsibilities:
- Build and maintain an integrated research roadmap translating individual project plans into a unified view of experiments, model/data readiness, system integrations, releases, dependencies, and critical paths.
- Connect model development to downstream use by coordinating transitions from pre-training through post-training, applied engineering, evaluation, and deployment; align handoff criteria and readiness expectations.
- Synchronize data, compute, and hardware by anticipating when training datasets, collection systems, robots, workcells, and GPU capacity are needed; manage resource forecasts and scheduling trade-offs.
- Drive blockers to resolution by identifying cross-team gaps early, convening the right owners, maintaining action plans, and escalating trade-offs with concrete recommendations.
- Surface capacity and staffing risks to research leaders, helping them understand where milestones need additional engineering capacity or expertise.
- Build lightweight execution rhythms through focused program reviews, decision/dependency logs, and concise updates for technical leadership.
- Manage uncertainty intelligently by distinguishing experiments, proof-of-concept work, engineering-readiness milestones, and customer commitments; track confidence and learning goals.
- Improve cross-functional execution by partnering with hardware and operations teams to clarify interfaces, ownership, acceptance criteria, and release expectations.
You will work closely with Research leadership, technical leads, infrastructure, robotics, and hardware teams. You won't invent the scientific roadmap yourself, but you must be technical enough to understand it, challenge assumptions constructively, and turn ambiguity into practical options.
REQUIREMENTS:
- Significant technical program management experience delivering complex, interdependent work across software, ML, research infrastructure, robotics, or similarly technical organizations; senior or staff-level judgment required.
- Strong understanding of the machine learning development lifecycle, including datasets, model training, evaluation, iteration, and practical challenges of moving models into production.
- Demonstrated ability to build an execution system from ambiguous starting points, identify true critical dependencies, and drive progress across teams without direct reporting authority.
- Technical fluency sufficient to work credibly with researchers and infrastructure engineers, ask the right questions, and present real trade-offs.
- Experience coordinating constrained engineering resources such as compute capacity, test systems, labs, hardware platforms, or specialized teams.
- Excellent written and verbal communication, including ability to turn many threads of technical work into concise, decision-ready views for leadership.
- Sound judgment about when to solve coordination issues independently, when to involve technical owners, and when decisions need leadership attention.
NICE TO HAVE:
- Experience in large-scale model training, foundation models, generative models, computer vision, embodied AI, or robotics.
- Familiarity with GPU clusters, data pipelines, robot testing/evaluation, or hardware/software integration.
- Experience bridging research organizations and customer-facing applied engineering or model release functions.
