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Robot Perception Jobs in Nevada (NOW HIRING)

Physical AI Senior Manager

Las Vegas, NV · On-site

$120K - $159K/yr

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 ...

Controls Engineer

Henderson, NV

$80K - $104K/yr

Create, maintain and review drawing packages for conveyor, robot and process systems. * Responsible ... depth perception, and the ability to adjust focus. Note: The statements herein are intended to ...

Controls Engineer

Henderson, NV · On-site

$80K - $104K/yr

Create, maintain and review drawing packages for conveyor, robot and process systems. * Responsible ... depth perception, and the ability to adjust focus. Note: The statements herein are intended to ...

Controls Engineer

Henderson, NV · On-site

$80K - $104K/yr

Create, maintain and review drawing packages for conveyor, robot and process systems. * Responsible ... depth perception, and the ability to adjust focus. Note: The statements herein are intended to ...

Controls Engineer

Henderson, NV · On-site

$80K - $104K/yr

Create, maintain and review drawing packages for conveyor, robot and process systems. * Responsible ... depth perception, and the ability to adjust focus. Note: The statements herein are intended to ...

Controls Engineer

Henderson, NV

$80K - $104K/yr

Create, maintain and review drawing packages for conveyor, robot and process systems. * Responsible ... depth perception, and the ability to adjust focus. Note: The statements herein are intended to ...

Execute structured scenario-based testing using track infrastructure and robotic platforms ... perception. * Utilize Vector tools (CANalyzer/CANoe) for live debugging, signal tracing, and post ...

Execute structured scenario-based testing using track infrastructure and robotic platforms ... perception. * Utilize Vector tools (CANalyzer/CANoe) for live debugging, signal tracing, and post ...

Execute structured scenario-based testing using track infrastructure and robotic platforms ... perception. * Utilize Vector tools (CANalyzer/CANoe) for live debugging, signal tracing, and post ...

Design and execute test campaigns for self-driving features (perception, planning, and control ... Bachelor's degree or higher in Engineering, Robotics, ECE, Computer Science, or a relevant ...

Design and execute test campaigns for self-driving features (perception, planning, and control ... Bachelor's degree or higher in Engineering, Robotics, ECE, Computer Science, or a relevant ...

Design and execute test campaigns for self-driving features (perception, planning, and control ... Bachelor's degree or higher in Engineering, Robotics, ECE, Computer Science, or a relevant ...

Sr AI/ML Engineer

Sparks, NV

$106K - $146K/yr

Develop signal processing, perception, and planning pipelines supporting MPC control loops. * Use ... Background in autonomous systems, robotics, or sensor fusion. * Familiarity with Agile/DevOps ...

Robot Perception information

What is robot perception?

Robot perception refers to the ability of robots to interpret and understand their environment using sensors and algorithms. This field involves processing data from cameras, lidar, radar, and other sensors to recognize objects, map surroundings, and make decisions. Effective robot perception is essential for tasks like navigation, object manipulation, and autonomous operation in dynamic environments. It combines elements of computer vision, machine learning, and sensor fusion to enable robots to function reliably and safely.

What are the key skills and qualifications needed to thrive in a Robot Perception role, and why are they important?

To excel in Robot Perception, you need a strong background in computer vision, machine learning, and sensor data processing, typically backed by a degree in computer science, robotics, or a related field. Familiarity with tools like ROS (Robot Operating System), OpenCV, PCL, and deep learning frameworks such as TensorFlow or PyTorch, as well as experience with LiDAR and camera systems, is highly valued. Creative problem-solving, adaptability, and effective teamwork are crucial soft skills for addressing complex perception challenges in dynamic environments. These competencies enable the development of robust perception systems, which are essential for safe and autonomous robotic operation.

What is the difference between Robot Perception vs Robot Software Engineer?

AspectRobot PerceptionRobot Software Engineer
Required CredentialsBachelor's or Master's in Robotics, Computer Science, or related fields; knowledge of perception algorithmsBachelor's or Master's in Software Engineering, Computer Science; programming skills in C++, Python
Work EnvironmentResearch labs, robotics companies, industrial settings focusing on sensor data processingSoftware development teams, robotics companies, embedded systems environments
Industry UsageUsed in autonomous vehicles, service robots, industrial automation for sensor data interpretationDevelops robot control software, integrates perception modules, and ensures system functionality

Robot Perception specialists focus on processing sensor data to enable robots to understand their environment, while Robot Software Engineers develop the software systems that control robot functions, including perception modules. Both roles often collaborate but have distinct focuses within robotics development.

What are some common challenges faced by professionals in Robot Perception roles, and how can they be addressed?

Professionals in Robot Perception roles often encounter challenges such as dealing with noisy sensor data, ensuring real-time processing, and integrating data from multiple sources to create an accurate understanding of the environment. Addressing these requires strong skills in sensor fusion, robust algorithm design, and close collaboration with robotics engineers and software developers. Continuous learning and staying updated with advancements in machine learning and computer vision are also key to overcoming these challenges and contributing effectively to the team's goals.
What are popular job titles related to Robot Perception jobs in Nevada? For Robot Perception jobs in Nevada, the most frequently searched job titles are:
Physical AI Senior Manager

Physical AI Senior Manager

Deloitte

Las Vegas, NV • On-site

$120K - $159K/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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