Physical AI Senior Manager - Manufacturing & Supply Chain
We are a team of strategic advisors, architects, and implementers who drive business transformations. Our diverse talent energizes clients' business functions and technology to maximize value in Supply Chain enhancing their ability to fulfill their growth and efficiency ambitions. Imagine working with world-class supply network capabilities like Smart Factory, Strategy & Innovation, Supply Chain Responsiveness, Sourcing & Procurement, or Product Development & Operations!
Are you ready to take your career to new heights? Join our US Supply Chain & Network Operations Offering, where you'll deliver transformational solutions using operational expertise, digital technologies, advanced analytics, and industry-specific hybrid solutions. Don't miss the chance to be part of a team that provides exceptional client value while advancing your professional journey. Apply now and become a vital part of our innovative and dynamic workforce!
Recruiting for this role ends on 5/31/26.
The team
You will join a cross-functional Supply Chain & Manufacturing consulting environment focused on helping clients modernize operations through technology, data, and advanced engineering. The role operates in a matrix of industry practitioners, technologists, and alliance partners and requires strong collaboration, structured problem-solving, and the ability to translate emerging technology into operational results.
Work you'll do
You will serve as the functional and domain expert for Physical AI-where AI meets the physical world-across manufacturing and supply chain operations. You will shape advisory engagements, lead proofs of concept (PoCs), and drive implementation programs that combine robotics, computer vision, simulation, digital twins, synthetic data, and edge AI, frequently in partnership with ecosystem alliance providers (e.g., NVIDIA, Siemens, AWS and others).
You will succeed if you are:
Comfortable in factories, warehouses, and leadership conference rooms
Can translate between controls engineers, data scientists, and frontline operations
Carry a strong bias to measurable outcomes, not demos
Write clearly, create usable assets, and mentor others
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 $175,300 - $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: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html
SCNOFY26
EPCORE
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.
