We are seeking a Product Manager, Data Strategy & Physical AI to define and execute the long-term product vision for FAR's AI-powered robotics platform. The intersection of foundation models and physical intelligence is creating a once-in-a-generation opportunity to reimagine how intelligent systems perceive, reason, and act in the real world. We need a visionary product leader who can treat data as our primary competitive moat and translate research frontiers into scalable, production-grade capabilities.
In this role, you will champion our core data strategy for foundation model creation, building a partner and tool ecosystem to systematically acquire, label, and iteratively improve physical AI datasets. You will architect a continuous data collection flywheel across deployed robot fleets, transforming real-world kinematics, video, and force-torque telemetry from edge operations back into high-fidelity training tokens. Recognizing the limitations of real-world environments, you will also lead the strategy to create high-fidelity synthesized datasets, utilizing advanced physics engines and simulation to generate diverse training tokens at massive scale.
Key job responsibilities
Data Acquisition & Labeling Ecosystem: Establish the partnerships, tools, and vendor pipelines necessary to acquire, curate, and continuously label multi-modal datasets for training large-scale models.
Fleet Data Flywheel Infrastructure: Architect the framework for a continuous data flywheel that securely streams high-frequency kinematics, egocentric video, and force-torque telemetry from real-world robot fleets back into the training loop.
Synthetic Data & Simulation Strategy: Define the strategy for generating high-fidelity, physics-aligned synthesized datasets using advanced simulation environments to scale training tokens for edge-case scenarios and long-horizon tasks.
Data Compliance & Governance: Partner with operations, privacy, legal, and security teams to build enterprise-grade data management pipelines that programmatically enforce data minimization, anonymization, and CCPA/GDPR compliance.
Data Quality & Token Curation: Implement automated telemetry filtering and dataset pruning strategies to identify high-value operational logs, eliminate redundant fleet data, and optimize training compute costs.
Cross-Functional Physical AI Delivery: Act as the strategic bridge between machine learning research scientists, simulation developers, robotics engineers, and hardware teams to deliver data-ready platform features that improve physical reliability.
BASIC QUALIFICATIONS
- Bachelor's degree in Computer Science, Engineering, or a related technical field
- Experience with feature delivery and tradeoffs of a product
- Experience with AI/ML technologies
- 10+ years of experience in technical product management
- Experience leading AI/ML platform or robotics product strategy
- Experience owning/driving roadmap strategy and definition for AI/ML or robotics systems
PREFERRED QUALIFICATIONS
- Experience in robotics design, automation systems development, control systems design, or related product development
- Advanced degree (MS/PhD) in AI, Machine Learning, Robotics, Computer Science, or a quantitative field
- Experience building and scaling AI/ML platforms (MLOps, model training infrastructure, data pipelines) from zero-to-one
- Experience working at the intersection of AI research and product commercialization - translating frontier science into customer-facing products
- Demonstrated ability to partner with research scientists and lead through ambiguity in fast-moving technical domains
- Experience with foundation models, deep learning systems, or computer vision at scale
- Entrepreneurial experience building AI-first products or founding AI-focused ventures
