Product Manager, Data & Teleoperation
Mind Robotics, Palo Alto, CA, United States
Mind Robotics is building intelligent robotics for industrial deployment. We believe the fastest path to broadly capable robots is through clearly defined, high-impact environments. We are starting where the need is most acute and the environment is most exacting: the factory floor.
Role Summary
The Product Manager for Data & Teleoperation sits at the intersection of human intent and robotic embodiment, treating the end-to-end data collection pipeline as a high-fidelity product. Your mission is to define and execute the roadmap for our teleoperation platform, ensuring that human demonstrations translate into the high-quality data necessary to ground our AI models in physical reality. You will bridge the gap between AI Research, Engineering, and Operations to build a scalable data flywheel that validates hardware and evaluates policy stability.
Key Responsibilities
Product Strategy & Roadmap
Teleoperation Platform Roadmap:
Own the product vision and multi-quarter roadmap for teleoperation "cockpits," prioritizing features like VR integration, haptics, and ultra-low-latency streaming to improve operator intuition.
Feature Definition & Hardware UX:
Translate hardware iteration needs (gripper design, field-of-view) into product requirements for the teleoperation interface, ensuring hardware is validated through rapid human feedback loops.
Technological Innovation:
Research and scope cutting-edge technologies, including VR, haptics, and ultra-low-latency streaming to enhance operator intuition.
Data Product Lifecycle
Data Fidelity & Integrity:
Define specifications for high-fidelity data capture, ensuring kinematics and latency parameters meet the standards required for robot-learnable datasets.
Recovery & Edge-Case Strategy:
Productize the "recovery data" program, defining workflows for operator intervention when autonomous policies fail to capture high-value training data.
Scale & Integration:
Oversee the strategic roadmap for Sim-to-Real data pipelines and passive factory video capture, ensuring a pathway to warehouse-scale operations.
KPI & Value Measurement
Metric Ownership:
Establish and track North Star metrics for the teleoperation program, including data collection throughput, cost-per-hour of high-value data, and operator efficiency.
Data Value Attribution:
Implement frameworks (e.g., Shapley values) to measure the impact of specific data sources on model performance, driving ROI-based data collection.
Quality over Quantity:
Monitor the "Quality" of the data output, ensuring it meets the rigorous benchmarks set by AI Research for model training.
Qualifications
Background:
5+ years in Product Management, ideally within Robotics, HRI, or data-intensive Infrastructure products.
Product Craft:
Expert in PRD creation, roadmap prioritization, and managing complex cross-functional dependencies across hardware and software cadences.
Strategic Vision:
Ability to treat data collection as a product, balancing immediate operational needs with the long-term goal of a productized data collection system.
Leadership:
Proven track record of earning trust on the factory floor and in the research lab, translating between technical disciplines and business objectives.
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Role Summary
The Product Manager for Data & Teleoperation sits at the intersection of human intent and robotic embodiment, treating the end-to-end data collection pipeline as a high-fidelity product. Your mission is to define and execute the roadmap for our teleoperation platform, ensuring that human demonstrations translate into the high-quality data necessary to ground our AI models in physical reality. You will bridge the gap between AI Research, Engineering, and Operations to build a scalable data flywheel that validates hardware and evaluates policy stability.
Key Responsibilities
Product Strategy & Roadmap
Teleoperation Platform Roadmap:
Own the product vision and multi-quarter roadmap for teleoperation "cockpits," prioritizing features like VR integration, haptics, and ultra-low-latency streaming to improve operator intuition.
Feature Definition & Hardware UX:
Translate hardware iteration needs (gripper design, field-of-view) into product requirements for the teleoperation interface, ensuring hardware is validated through rapid human feedback loops.
Technological Innovation:
Research and scope cutting-edge technologies, including VR, haptics, and ultra-low-latency streaming to enhance operator intuition.
Data Product Lifecycle
Data Fidelity & Integrity:
Define specifications for high-fidelity data capture, ensuring kinematics and latency parameters meet the standards required for robot-learnable datasets.
Recovery & Edge-Case Strategy:
Productize the "recovery data" program, defining workflows for operator intervention when autonomous policies fail to capture high-value training data.
Scale & Integration:
Oversee the strategic roadmap for Sim-to-Real data pipelines and passive factory video capture, ensuring a pathway to warehouse-scale operations.
KPI & Value Measurement
Metric Ownership:
Establish and track North Star metrics for the teleoperation program, including data collection throughput, cost-per-hour of high-value data, and operator efficiency.
Data Value Attribution:
Implement frameworks (e.g., Shapley values) to measure the impact of specific data sources on model performance, driving ROI-based data collection.
Quality over Quantity:
Monitor the "Quality" of the data output, ensuring it meets the rigorous benchmarks set by AI Research for model training.
Qualifications
Background:
5+ years in Product Management, ideally within Robotics, HRI, or data-intensive Infrastructure products.
Product Craft:
Expert in PRD creation, roadmap prioritization, and managing complex cross-functional dependencies across hardware and software cadences.
Strategic Vision:
Ability to treat data collection as a product, balancing immediate operational needs with the long-term goal of a productized data collection system.
Leadership:
Proven track record of earning trust on the factory floor and in the research lab, translating between technical disciplines and business objectives.
#J-18808-Ljbffr