Dyna Robotics builds general-purpose robots powered by a proprietary embodied AI foundation model with top-in-industry generalization and real-world performance. Already deployed with customers across multiple industries, our robots do commercial-grade work in the physical world. Our team comes from Google DeepMind, Meta, and Cruise, and we're backed by CRV, First Round, and other leading investors.

We’re looking for a Research Technical Program Manager with a strong research background in robotics to help guide and coordinate our research portfolio.

You’ll be the person who knows where our research stands: what each team is pursuing, what the evidence shows, how projects relate to one another, and where decisions or support are needed. Working closely with the Chief Research Officer, you’ll turn that understanding into clear priorities, sound technical judgments, and an actionable research strategy.

The role calls for scientific depth, good judgment, and the ability to help teams keep making progress through the uncertainty inherent in research.

This is a full-time, on-site position in Redwood City.

What You’ll Do

Portfolio Visibility: Maintain a complete view of the portfolio. Track each project’s objectives, hypotheses, results, milestones, risks, and upcoming decisions.

Progress Assessment: Assess progress with researchers. Evaluate the strength of results, separate meaningful advances from open questions, and surface technical bottlenecks early.

Cross-Team Connections: Connect work across teams. Spot shared challenges, dependencies, and complementary approaches, and find opportunities to bring separate projects together.

Research Strategy: Partner with the Chief Research Officer on strategy. Synthesize findings, develop recommendations, and support decisions on research direction, priorities, resourcing, and new opportunities.

Research Planning: Turn strategy into research plans. Help teams define tractable questions, useful evaluation criteria, and milestones that reflect both scientific uncertainty and organizational goals.

Decisions & Follow-Through: Drive decisions and follow-through. Lead research reviews, clarify tradeoffs, document decisions, and make sure every team has clear ownership and next steps.

Leadership Updates: Keep leadership informed. Deliver concise, evidence-based updates that give an accurate picture of progress and show where leadership’s attention is needed.

Research-to-Application: Bridge research and application. Work with engineering and product teams to identify when promising findings are ready for further development and what validation remains.

What You’ll Bring

Research Background: A strong research background in robotics, shown through original research, publications, or substantial contributions in an industry research setting.

Technical Expertise: Deep expertise in one or more areas such as robot learning, manipulation, perception, planning, control, embodied AI, or autonomous systems.

Technical Engagement: The ability to engage deeply with technical work: questioning assumptions, interpreting experimental results, and exercising sound judgment beyond your own specialty.

Research Coordination: Experience coordinating complex research efforts across multiple researchers, teams, or disciplines.

Strategic Thinking: You can connect individual projects to broader research goals and articulate the implications of different choices.

Comfort with Ambiguity: Comfort with ambiguity and changing evidence, and the judgment to adapt plans as the research evolves.

Communication & Influence: Clear communication, strong organization, and the ability to build trust and influence across teams.

Bonus Points For

Education: A PhD in robotics, computer science, electrical engineering, mechanical engineering, or a related field, or equivalent research experience.

Research Leadership Partnership: Experience working with senior research leadership on portfolio planning and technical prioritization.

Physical Robotics Experience: Hands-on experience with physical robotic systems, including the challenges of experimentation, evaluation, and deployment.