Senior / Staff Technical Program Manager, AI Research

Rhoda AI • Mountain View, CA

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About The Position

Rhoda AI is hiring a Senior/Staff Technical Program Manager, AI Research to scale coordination and execution across research programs. This is a deeply technical, cross-functional role spanning pre-training, post-training, applied research, data, GPU infrastructure, robotic hardware, and customer-facing model delivery. The role owns the integrated execution plan across these efforts: connecting milestones, anticipating dependencies, resolving blockers, and helping teams make timely resource and sequencing decisions. The aim is to give researchers and engineers more time to build while making the path from research experiments to usable models more predictable.

The position works closely with Research leadership, technical leads, infrastructure, robotics, and hardware teams. It does not own the scientific roadmap, but requires enough technical understanding to constructively challenge assumptions and turn ambiguity into practical options.

Success means clarifying important handoffs, surfacing blockers early, resolving resource conflicts faster, reducing coordination across silos, and giving leadership a trustworthy view of milestones and risks.

Requirements

• Significant technical program management experience delivering complex, interdependent work across software, ML, research infrastructure, robotics, or similarly technical organizations, with senior- or staff-level judgment.
• Strong understanding of the machine learning development lifecycle, including datasets, model training, evaluation, iteration, and challenges in moving models into production.
• Demonstrated ability to build an execution system from an ambiguous starting point, identify critical dependencies, and drive progress across teams without direct reporting authority.
• Technical fluency to work credibly with researchers and infrastructure engineers, ask relevant questions, and present real trade-offs rather than merely collect status.
• Experience coordinating constrained engineering resources, such as compute capacity, test systems, labs, hardware platforms, or specialized teams.
• Excellent written and verbal communication, including the ability to turn multiple threads of technical work into a concise, decision-ready view for leadership.
• Sound judgment about when to resolve coordination issues independently, involve technical owners, or bring a decision to leadership.

Nice To Haves

• Experience in large-scale model training, foundation models, generative models, computer vision, embodied AI, or robotics.
• Familiarity with GPU clusters, data pipelines, robot testing and evaluation, or hardware/software integration.
• Experience bridging research organizations and customer-facing applied engineering or model release functions.

Responsibilities

• Build and continuously update an integrated research roadmap covering experiments, model and data readiness, system integrations, releases, dependencies, critical paths, and decision points.
• Coordinate transitions from pre-training checkpoints to post-training, applied model engineering, evaluation, and deployment; align on handoff criteria, owners, and readiness expectations.
• Anticipate the availability needs of training datasets, collection systems, robots, workcells, and GPU capacity; manage resource demand forecasts and routine scheduling trade-offs within agreed priorities.
• Identify cross-team gaps, convene the appropriate owners, maintain action plans and contingencies, and escalate consequential trade-offs with a concrete recommendation.
• Surface capacity and staffing risks early, helping research leaders understand when milestones require additional engineering capacity, specialized expertise, or reprioritization, without owning personnel management.
• Establish lightweight execution rhythms, including focused program reviews, decision and dependency logs, and concise updates for technical leadership.
• Track uncertainty appropriately by distinguishing experiments, proof-of-concept demonstrations, engineering-readiness milestones, and customer-deployment commitments, and by tracking confidence and learning goals.
• Partner with hardware and operations TPMs and program leads to clarify interfaces, ownership, acceptance criteria, and release expectations.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed