Model Program Manager

Join us to shape the next frontier of AI-driven robotics!

Dyna Robotics makes general-purpose robots powered by a proprietary embodied AI foundation model that generalizes and self-improves across varied environments with commercial-grade performance. Dyna's robots have been deployed at customers across multiple industries. Its frontier model has the top generalization and performance in the industry.

Dyna Robotics was founded by repeat founders Lindon Gao and York Yang, who sold Caper AI for $350 million, and former DeepMind research scientist Jason Ma. The company has raised over $140M, backed by top investors, including CRV and First Round.We're positioned to redefine the landscape of robotic automation.

Position Overview

As a Model Program Manager at Dyna Robotics, you will own cross-functional programs that turn task requirements into measurable robot capability for both internal milestones and customer deployments. You will drive end-to-end execution across research, engineering, and operations—defining what success looks like, translating goals into executable plans, and ensuring we make consistent progress through iteration cycles.

This role is accountable for outcomes, not just coordination. You will run multiple programs in parallel and continuously improve how we execute—clarifying interfaces between teams, defining operational standards, and landing process improvements that increase speed and reliability. You will define requirements and push changes that make every step of the workflow easier to run and easier to scale.

What You Will Do

• Define clear success criteria for new projects and milestones, aligning stakeholders on KPIs.

• Design and run end-to-end robot learning programs, including data collection plans, labeling/annotation requirements, evaluation design, and overall execution.

• Coordinate cross-functional iteration cycles by aligning owners, schedules, dependencies, and priorities across research, engineering, and data operations.

• Establish and maintain operating cadence for ongoing work, including progress tracking, issue escalation, decision documentation, and stakeholder communication.

• Improve the systems that support robot learning by creating clear specs, instructions, QA checks, and processes that increase speed and reliability.

What You’ll Bring

• 8+ years of experience running complex technical programs or operational workflows end-to-end with measurable outcomes.

• Experience working in technical environments and collaborating closely with engineers and/or researchers to deliver ambiguous projects.

• Strong systems thinking with a track record of turning messy problems into simple, scalable processes.

• Experience working with operators, technicians, or frontline teams and designing workflows that work in real conditions.

• Strong written communication skills, including the ability to write clear specs, instructions, and process documentation.

• Strong analytical and strategic judgment with a bias toward action and delivery.

• Comfort operating independently in ambiguous environments with high ownership and accountability.

Bonus Points For

• Familiarity with basic ML concepts.

• Experience in AI robotics labs or robotics product environments, especially where hardware, software, and operations intersect.

• Experience with on-robot evaluation, test planning, and/or benchmarking.

• Experience building or running data collection and labeling/annotation programs.

• Experience working in a fast-paced startup environment with high ownership and limited structure.

At Dyna Robotics, we build technology for the real world, which requires a team as diverse as the environments our robots inhabit. We are an equal opportunity employer committed to technical rigor and mutual respect.

Don’t let a checklist stop you. Data shows that underrepresented groups often only apply if they meet 100% of the criteria. We value problem-solving and grit over keyword matching. If you’re passionate about the intersection of geometry and robotics, we want to hear from you—even if you don't check every box.