TELUS Digital · Denver
Product & ProgramAI Digital SolutionsRemoteFullTimeposted 5w ago
Welcome to TELUS Digital — where innovation drives impact at a global scale. As an award-winning digital product consultancy and the digital division of TELUS, one of Canada’s largest telecommunications providers, we design and deliver transformative customer experiences through cutting-edge technology, agile thinking, and a people-first culture.
With a global team across North America, South America, Central America, Europe, and APAC, we offer end-to-end expertise across eight core service areas: Digital Product Consulting, Digital Marketing Services, Data & AI, Strategy Consulting, Business Operations Modernization, Enterprise Applications, Cloud Engineering, and QA & Test Engineering.
From mobile apps and websites to voice UI, chatbots, AI, customer service, and in-store solutions, TELUS Digital enables seamless, trusted, and digitally powered experiences that meet customers wherever they are — all backed by the secure infrastructure and scale of our multi-billion-dollar parent company.
Robotics 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.
This role will operate remotely out California and require regular travel to various data collection sites.
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.
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.
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.
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