Physical AI Senior Manager
Key responsibilities
- 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.
The team Qualifications Required
- 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)
- 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.
Preferred
- Experience collaborating with technology partners (e.g., NVIDIA, Siemens, AWS. and/or similar ecosystems) to translate platforms into deliverable architectures and programs.
- Manufacturing and supply chain technology exposure in areas such as sensing and IIoT connectivity, process and product optimization, automation and process control, fleet operations, machine learning and data science, cybersecurity for OT
- Demonstrated experience leading client-facing advisory, PoCs, and implementations (not just research), including requirements, acceptance criteria, and operational handover.
- Graduate degree (MS/PhD) in Robotics, Computer Science, Electrical/Mechanical Engineering, Industrial Engineering, Applied Physics, Operations Research, or related field.
- Hands-on experience with NVIDIA ecosystem elements relevant to Physical AI (e.g., accelerated computing for vision/AI at the edge, simulation workflows, robotics stacks) and Siemens engineering platforms and tooling; ability to compare and compose with other vendor stacks.
- Experience designing governance and operating models for Physical AI in production: model monitoring and drift, incident response, data management, human-in-the-loop, safety and controls integration.
- Demonstrated thought leadership: reusable accelerators, reference architectures, demo assets, publications, or enablement delivered to internal/external audiences.
- Business development contribution (pipeline creation, proposal leadership, account expansion) and executive stakeholder management.
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $171,600 - $322,900. You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. Information for applicants with a need for accommodation: SCNOFY27#EPCORE
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