The OpportunityRobotics foundation models need millions of hours of dense, real-world data-and simulation alone won't cut it. TELUS Digital is solving the Physical AI bottleneck, capturing highly calibrated, real-world data at scale across hundreds of devices to power the world's leading hyperscalers.
We are hiring a Product Manager for the Physical AI Robotics product team. You will own the tooling this runs on: capture applications, operator workflows, session management, review and QA, and customer delivery. You will work with the researchers consuming the data and the operators producing it, and the standards you set will carry into how the industry does this.
Your application will stand out if you are demonstrably curious and have side work projects to showcase.
Location & Flexibility This role can operate remotely out of the United States but will require regular travel to various data collection sites.
Why Join Us?- Early market: Standards for physical AI data are not set yet. You will have a hand in setting them.
- Impact at scale: Hundreds of devices in the field and an operator base large enough that a design change shows up in the numbers within a week.
- Hard/Unsolved problems: Capture design, quality definition, and operator experience for a data type most of the industry cannot produce.
Responsibilities - Own the roadmap for robotics data collection, setting direction and driving execution across engineering, design, operations, quality, and solutions.
- Assess demand for new capture modalities, then define the collection model, hardware, and tooling.
- Work with engineering and design on the operator experience: onboarding, task guidance, in-session feedback, error states, review workflows. Operators work one-handed, in motion, wearing a headset, or against a clock.
- Build prototypes and write the specs. Requirements and user stories that hold up under engineering review.
- Translate customer model requirements into collection designs, and evolving research into quality standards for egocentric data: pose accuracy, sync tolerance, occlusion handling, annotation schema, acceptance criteria.
- Spend time with collectors, session leads, and reviewers. When data underperforms in training, trace it back to the capture design or the tooling that produced it.
- Represent the product directly to hyperscaler and robotics foundation model teams, and bring their constraints back into the roadmap.
- Optimize for yield per session, rejection rate, cost per usable hour, capture-to-delivery time, and operator retention.
- Champion pilots as the default way to test a change. Small cohort, clear hypothesis, fixed window. Scale what works and stop what does not.
Qualifications- 4+ years in product management, including at least 2 in robotics, physical AI, AR/VR, autonomous systems, or data collection at scale.
- Technical degree, or equivalent experience. Past work as a software engineer or researcher is a plus.
- Technical depth to hold a real conversation with a research team.
- Direct experience with one or more of: egocentric or wearable data capture, teleoperation systems, robot data pipelines, multi-sensor collection rigs or similar setups
- Experience defining product vision and roadmaps in ambiguous, fast-moving environments.
- Hands-on robotics background. Robotics, ML engineer on embodied models, teleoperation engineer, or similar.
- Familiarity with imitation learning, VLA models, or manipulation policy training, and the data those methods need.
- Experience managing distributed human operations, including crowd or contractor workforces.
- You have shipped something physical and understand calibration, sensor sync, and coordinate frames, and how they fail.
