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Physics Ai Simulation Jobs in Wisconsin (NOW HIRING)

Physical AI Senior Manager

Milwaukee, WI · On-site

$124K - $164K/yr

Simulation, digital twins, physics-based modeling for factories, lines, cells, warehousing, and ... Edge AI deployment (e.g., performance, reliability, lifecycle operations) * Manufacturing and ...

Develop ion optical simulation tools to predict overall instrument performance * Validate ... MS or PhD in Materials Science, Engineering, Physics, or a related field (required) * 6-8 years of ...

Develop ion optical simulation tools to predict overall instrument performance * Validate ... Strong foundation in engineering, physics, and materials science principles * Experience with ion ...

Our students benefit from concrete projects, simulations, workshops and design challenges that ... Space navigation, autonomous systems and AI in space * Space weather Competences - titre ...

Physics Ai Simulation information

What engineers make $500,000?

Senior engineers in specialized fields such as aerospace, petroleum, or software engineering can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries. Roles involving leadership, project management, or working in lucrative markets often contribute to such high compensation levels.

How do professionals in Physics AI Simulation typically collaborate with other teams to develop accurate models?

In Physics AI Simulation roles, collaboration is integral to creating reliable simulation models. Professionals often work closely with domain experts, such as physicists and engineers, to validate the scientific accuracy of their AI-driven simulations. They also partner with software developers to integrate simulation tools into broader platforms and may engage with data scientists to refine algorithms using experimental or real-world data. Regular interdisciplinary meetings and code reviews are common practices to ensure alignment and quality throughout the project lifecycle.

What are the key skills and qualifications needed to thrive as a Physics AI Simulation Specialist, and why are they important?

To thrive as a Physics AI Simulation Specialist, you need a solid background in physics, mathematics, and computer science, often supported by a relevant degree or advanced studies. Familiarity with simulation software such as MATLAB, Simulink, or Unity, and programming languages like Python or C++, is typically required, along with experience in machine learning frameworks. Strong problem-solving, analytical thinking, and effective collaboration skills help distinguish top performers in this field. These competencies ensure accurate modeling, innovative solutions, and effective teamwork in developing realistic and efficient AI-driven simulations.

Can a physicist become an AI engineer?

A physicist can become an AI engineer by acquiring skills in programming, machine learning, and data analysis, often through online courses or advanced degrees. Their strong analytical and mathematical background can be a valuable asset in developing AI models and algorithms.

Which 3 jobs will survive AI?

Physics AI Simulation professionals are likely to see continued demand in roles involving complex problem-solving, data analysis, and developing AI models that require deep domain expertise. Jobs that involve creativity, emotional intelligence, and tasks requiring human judgment, such as research scientists, AI ethics specialists, and technical educators, are also expected to persist. These roles benefit from specialized knowledge and skills that are difficult for AI to fully replicate.

What is a Physics AI Simulation job?

A Physics AI Simulation job involves creating, developing, and maintaining computer simulations that model physical systems using artificial intelligence techniques. Professionals in this field use their expertise in physics, mathematics, and programming to design simulations for research, engineering, gaming, or educational purposes. They often work with machine learning algorithms to improve the accuracy and efficiency of these simulations, enabling better predictions and deeper insights into complex phenomena. This role typically requires strong analytical skills and experience with simulation software and programming languages.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior AI researcher, machine learning director, or AI architect, often requiring advanced skills in programming, data analysis, and deep learning. These roles are usually found in leading tech companies or specialized research organizations and may involve managing large projects or teams. Compensation at this level reflects extensive experience, expertise, and leadership responsibilities in the AI field.

What is the difference between Physics Ai Simulation vs Data Scientist?

AspectPhysics Ai SimulationData Scientist
Required CredentialsPhysics or Computer Science degree, knowledge of AI and simulation toolsStatistics, Mathematics, Computer Science degree, programming skills
Work EnvironmentResearch labs, tech companies, simulation software developmentBusiness, tech firms, data analysis teams
Industry UsagePhysics research, AI-driven simulations, scientific modelingData analysis, predictive modeling, business insights

Physics Ai Simulation focuses on creating AI-driven models to simulate physical phenomena, often requiring physics and AI expertise. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles involve data and AI, Physics Ai Simulation emphasizes physical modeling and simulation, whereas Data Scientists focus on data analysis and interpretation.

What are popular job titles related to Physics Ai Simulation jobs in Wisconsin? For Physics Ai Simulation jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Physics Ai Simulation jobs? Cities in Wisconsin with the most Physics Ai Simulation job openings:
Infographic showing various Physics Ai Simulation job openings in Wisconsin as of July 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution.
Physical AI Senior Manager

Physical AI Senior Manager

Deloitte

Milwaukee, WI • On-site

$124K - $164K/yr

Other

Posted 22 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 91 frontline employees who took The Breakroom Quiz

58th of 150 rated financial services


Job description

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 8/31/26.

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). Candidates should be comfortable in factories, warehouses, and leadership conference rooms with the experience to translate between controls engineers, data scientists, and frontline operations.

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:https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

SCNOFY27

#EPCORE

Qualifications:

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 8/31/26.

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). Candidates should be comfortable in factories, warehouses, and leadership conference rooms with the experience to translate between controls engineers, data scientists, and frontline operations.

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....

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