Physical AI Senior Manager

Work you’ll do

• Lead Physical AI strategy and advisory for manufacturing and supply chain clients. Identify high-value use cases (e.g., quality inspection, safety, intralogistics, material handling, asset monitoring, autonomous operations), define value hypotheses, and translate to roadmaps and business cases.
• Own solution shaping and end-to-end architecture spanning sensors, vision, data pipelines, model development, simulation, edge deployment, and operations (i.e., MLOps and ModelOps), with explicit acceptance criteria for operational environments.
• Drive PoCs and pilots to measurable outcomes. Define experiments, data collection plans, synthetic data approaches (when appropriate), evaluation metrics, and scale plans from pilot-to-plant and factory/network rollout.
• Integrate AI with real-world constraints: latency, reliability, safety, OT/IT connectivity, cybersecurity, model drift, human-in-the-loop workflows, and maintenance/operating model considerations.
• Partner with alliances and product teams to translate partner platforms into client-ready reference architectures, demos, and repeatable delivery assets.
• Influence pursuits and proposals: support scoping, estimating, staffing, risk and assumption framing, and executive-level storytelling. Serve as technical authority in client workshops and due diligence.
• Lead and mentor multi-disciplinary teams: data science, ML engineering, software and edge, vision, robotics and controls, manufacturing experts, and contribute to capability-building and market activation.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 10+ years of relevant experience, including client leadership, team leadership, and sustained contribution to business development/pursuits.
• Experience in at least two of the following domains:
• Computer vision for industrial environments (e.g., inspection, defect detection, safety, tracking, manufacturing assembly)
• Robotics and autonomy (e.g., industrial robotics, mobile robotics and AMRs, perception-to-action workflows)
• Simulation, digital twins, physics-based modeling for factories, lines, cells, warehousing, and logistics (e.g., discrete event, physics, MILP)
• Synthetic data generation and validation approaches for model development
• Edge AI deployment (e.g., performance, reliability, lifecycle operations)
• Making manufacturing and supply chain domain experience in areas such as discrete or process manufacturing, quality systems, maintenance and reliability, intralogistics, warehouse operations, plant OT/IT constraints, safety, and compliance.
• Ability to travel up to 50%, based on the work you do and the clients and industries/sectors you serve
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.