Technical practice
How would you decide when to use behavior cloning versus reinforcement learning for a dexterous robot task?
What to coverThe role calls for deploying both approaches with high success rates. Suggested preparation: Compare demonstration requirements, exploration costs, and how you would evaluate performance on real robots.
What trade-offs would you consider when training diffusion policies and vision-language-action models for manipulation?
What to coverThe posting explicitly names both model families. Suggested preparation: Discuss data needs, action generation, generalization, and deployment constraints without assuming a particular robot or model architecture.
How would you collect and assess teleoperated demonstrations for policy training?
What to coverThe posting asks for familiarity with teleoperation and leadership of data-collection infrastructure. Suggested preparation: Explain how you would assess demonstration quality, coverage, and consistency before training.
How would you structure software infrastructure spanning robot data collection and model training?
What to coverLeading infrastructure for data collection and training is a stated responsibility. Suggested preparation: Address reproducibility, traceability between datasets and models, and feedback from robot trials to subsequent training runs.
How would you integrate learned perception and control on a real robot?
What to coverThe role asks for experience developing and deploying both on real robots. Suggested preparation: Explain how you would handle uncertain observations, control-loop timing, and testing beyond offline model metrics.
Where would classical manipulation, control theory, and motion planning complement a learned policy?
What to coverThe posting explicitly seeks a strong foundation in all three areas. Suggested preparation: Describe how model-based constraints or planning might complement learned behavior, including trade-offs in robustness and flexibility.
How would you evaluate whether a dexterous policy achieves a high success rate?
What to coverHigh success rates for data-center tasks are an explicit focus. Suggested preparation: Define task success, representative test conditions, and failure categories; explain how you would distinguish repeatable performance from a promising demonstration.
What would you check when a policy works in training but fails during real-time robot operation?
What to coverThe role spans training, real-robot deployment, and real-time operation. Suggested preparation: Separate data-distribution issues from perception, timing, and control issues, then describe a systematic way to isolate the cause.
How would you turn a robotics-learning research advance into a production-ready system?
What to coverTranslating frontier research into production-ready robotics is a stated responsibility. Suggested preparation: Discuss evidence needed beyond a research result, including repeatability, operational constraints, and measured gains over an existing approach.
When might edge deployment or tactile sensing change a manipulation design?
What to coverBoth are listed as bonus experience, not core requirements. Suggested preparation: Discuss potential latency and feedback trade-offs, while making clear that their usefulness depends on the task and hardware.
Behavioural practice
Tell me about a time you led shared technical infrastructure while others depended on it.
What to coverThe role calls for leading software infrastructure for data collection, training, and real-time operation. Suggested preparation: Give a real situation, your actions to set priorities and coordinate work, and the resulting impact.
Describe an experiment that failed and changed your approach.
What to coverThe posting describes a small team with frequent experimentation and an emphasis on results. Suggested preparation: Explain the situation, what evidence you gathered and changed, and the result rather than presenting experimentation as success by itself.
Tell me about a time you moved a research idea toward a working robot system.
What to coverThe role emphasizes translating robotics-learning research into production-ready systems. Suggested preparation: Use a real example to explain the initial idea, the practical actions and trade-offs, and what ultimately worked or did not.
Describe a time you collaborated across disciplines to resolve a robotics problem.
What to coverThe stated work connects learning, perception, control, and robot operation in a small team. Suggested preparation: Identify the situation, your specific contribution and coordination, and the result without claiming sole credit for a team outcome.
Tell me about a time you took ownership of an ambiguous engineering decision.
What to coverThe posting describes a founding role with substantial influence over the engineering stack and no established instruction manual. Suggested preparation: Explain the situation, how you chose a direction and tested it, and what the outcome taught you.