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Product Manager, Data & Teleoperation

Mind Robotics - Palo Alto, California, United States

Posted Apr 20, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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401(k) match
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Market context

U.S. role benchmark (BLS OEWS)
$102,662 U.S. median for this role
Projected growth (BLS Employment Projections)
+5.4% - Faster than average

Matched to SOC 11-1021 - Product Management aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Product From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
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Weekend work
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Company

Company stage
Early From the posting source checked Jun 20, 2026

Application

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Assessment
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Deadline
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Where they hire

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About this role

Product Manager, Data & Teleoperation Palo Alto, California, 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

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