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Embodied Ai Jobs (NOW HIRING)

General Motors

Senior Manager, Embodied AI

Frankfort, KY · On-site +1

$296K - $453K/yr

... of Embodied AI. This role emphasizes day-to-day people management, technical guidance, and effective execution. You will contribute to the future of Autonomous Vehicle (AV) development by helping ...

Stord

Head of Embodied AI, Data Foundry

You will have end-to-end ownership of the early Embodied AI business-including the product, customers, data capture program, data operations, team, and P&L. This is a true builder-operator role . You ...

Samsung SDS Co.

Senior Physical AI Engineer

Mountain View, CA · On-site

$122K - $168K/yr

This role sits at the intersection of robotics, embodied AI, machine learning, and production software engineering. You will connect high-level AI models to physical robot behavior, enabling robots ...

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How much do embodied ai jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for embodied ai in the United States is $58.71, according to ZipRecruiter salary data. Most workers in this role earn between $52.64 and $68.27 per hour, depending on experience, location, and employer.

What is embodied AI?

Embodied AI refers to artificial intelligence systems that are integrated into physical entities, such as robots, which can perceive, act, and interact with the real world. Unlike traditional AI, which operates purely in digital environments, Embodied AI enables machines to understand and respond to their surroundings through sensors and actuators. This field combines elements of robotics, computer vision, natural language processing, and machine learning to create agents that can learn from their experiences and adapt to new tasks. Embodied AI is used for applications like autonomous vehicles, service robots, and interactive agents.

What are the common challenges faced by professionals working in embodied AI roles?

Professionals in Embodied AI often encounter challenges related to integrating physical hardware with complex AI algorithms. This can include troubleshooting issues between sensors, actuators, and software to ensure smooth real-world operation. Additionally, working in multidisciplinary teams—combining robotics, computer vision, and machine learning—requires strong collaboration and communication skills. Staying up-to-date with rapid advancements and testing models in unpredictable, real-world environments are also key aspects of the role.

What are the key skills and qualifications needed to thrive as an embodied AI engineer, and why are they important?

To thrive as an Embodied AI Engineer, you need a strong background in robotics, computer vision, machine learning, and programming languages such as Python or C++. Familiarity with robotics middleware (like ROS), simulation tools (such as Gazebo or PyBullet), and relevant AI frameworks is typically required, along with advanced degrees in computer science or engineering often preferred. Creative problem-solving, teamwork, and effective communication are key soft skills that set candidates apart in this interdisciplinary field. These skills and qualities are essential for developing intelligent systems that can physically interact with the world and adapt to complex, real-world environments.

What is the difference between Embodied Ai vs Robotics Engineer?

AspectEmbodied AiRobotics Engineer
Required CredentialsDegree in AI, Computer Science, or related fieldsDegree in Robotics, Mechanical, or Electrical Engineering
Work EnvironmentResearch labs, AI development firms, tech companiesManufacturing plants, research labs, engineering firms
Industry UsageAI-driven applications, virtual agents, autonomous systemsPhysical robot design, automation, hardware integration
Common Search/ComparisonFocuses on AI embodiment in virtual or physical agentsFocuses on hardware and mechanical aspects of robots

Embodied Ai primarily involves developing AI systems that can operate within physical or virtual agents, emphasizing AI algorithms and interaction. Robotics Engineers focus on designing and building physical robots, integrating hardware and software. While both roles overlap in AI and robotics, Embodied Ai centers on AI behavior within agents, whereas Robotics Engineers work on the physical construction and mechanics of robots.

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What cities are hiring for Embodied Ai jobs?

Cities with the most Embodied Ai job openings:

What states have the most Embodied Ai jobs?

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What are popular job titles for Embodied Ai?

Popular job titles for Embodied Ai:

Embodied Ai jobs near you
Infographic showing various Embodied Ai job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 77% Full Time, 19% Part Time, and 3% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $122,123 per year, or $58.7 per hour.

Member of Technical Staff - Simulation Engineer

San Francisco, CA • On-site

Moonlake AI
See more jobs at Moonlake AIexternal

Full-time

Re-posted 9 days ago

Key responsibilities

  • Design and develop simulation environments for robotics training and evaluation

  • Build simulation systems supporting perception, navigation, manipulation, and embodied AI tasks

  • Develop infrastructure supporting large-scale synthetic data generation and improve simulation workflows

Job description

Introducing Moonlake, AI for creating world simulations.
About Moonlake
Moonlake is building the frontier of interactive world models: systems that generate, simulate, and reason over 3D environments for robotics, embodied AI, and interactive applications.
We develop the infrastructure that enables intelligent systems to learn, evaluate, and interact within realistic virtual environments before operating in the physical world.
Our work sits at the intersection of:
  • Robotics
  • Embodied AI
  • Interactive 3D Worlds
  • World Models
  • Simulation Infrastructure
  • Physical AI

Moonlake is building the next generation of AI infrastructure for interactive digital worlds. Our mission is to enable anyone to create, simulate, and interact with rich environments using natural language and multimodal inputs, turning simple ideas into worlds with structure, physics, and intelligent behavior.
Our team has raised $28M in seed funding from NVIDIA Ventures, Threshold Ventures, AIX Ventures, and notable angels including Naval Ravikant and Jeff Dean to build the foundational layer for the future of AI-powering everything from robotics training and simulation to digital twins and interactive environments.
We are looking for exceptional engineers to help build the simulation systems that will power the next generation of robotics and embodied intelligence.
The Role
We're looking for a Member of Technical Staff - Simulation Engineer to build the simulation systems and infrastructure that power robotics and embodied AI.
This role focuses on developing high-fidelity simulation environments that accurately model robot behavior, sensors, physics, and real-world interactions. You'll build the simulation infrastructure used for robot learning, evaluation, synthetic data generation, and sim-to-real transfer.
You'll collaborate closely with teams working on robotics, world models, AI systems, and simulation infrastructure.
This is a highly hands-on software engineering role for builders who enjoy solving challenging problems across robotics, simulation, physics, and distributed systems.
What You'll Do
Build Robotics Simulation Systems
  • Design and develop simulation environments for robotics training and evaluation
  • Build simulation systems supporting perception, navigation, manipulation, and embodied AI tasks
  • Develop scalable simulation workflows that enable rapid experimentation and robot learning
  • Build reusable tooling that makes simulation development efficient and reliable
Improve Sim-to-Real Transfer
  • Compare simulation outputs against real-world robot behavior
  • Model robot dynamics, sensors, contacts, and environmental interactions
  • Tune simulation fidelity through calibration and validation
  • Improve policy transfer using calibration, benchmarking, and domain randomization techniques
Support Robot Learning
  • Partner with robotics and AI teams to build environments for training and evaluating intelligent systems
  • Develop infrastructure supporting large-scale synthetic data generation
  • Create simulation benchmarks for evaluating robotics models
  • Optimize simulation environments for machine learning workflows
Build Simulation Infrastructure
  • Develop production-quality software supporting simulation systems
  • Build tools that improve simulation reliability, testing, and scalability
  • Improve pipelines for simulation creation, execution, and evaluation
  • Optimize simulation performance while maintaining physical realism
Areas of Focus
Robotics Simulation
  • Physics simulation
  • Robot dynamics
  • Sensor simulation
  • Sim-to-real transfer
  • Robot learning environments
Simulation Infrastructure
  • Synthetic data generation
  • Simulation tooling
  • Environment automation
  • Performance optimization
  • Benchmarking and validation
Robotics
  • Perception
  • Manipulation
  • Navigation
  • Embodied AI
  • Physical reasoning
What We're Looking For
  • Experience building robotics simulation systems for robotics, autonomy, embodied AI, or physical AI
  • Experience with robotics simulators such as Isaac Sim, MuJoCo, PyBullet, Gazebo, Drake, or equivalent
  • Understanding of robot dynamics, physics simulation, sensor modeling, and sim-to-real transfer
  • Strong software engineering skills in Python, C++, or similar languages
  • Experience building production-quality simulation software and infrastructure
  • Experience writing reliable, maintainable, and well-tested code
  • Strong systems thinking and problem-solving skills
  • Ability to work closely with robotics, machine learning, and research teams
Nice to Have
  • Experience with NVIDIA Isaac Sim or Omniverse
  • Experience generating synthetic data for robotics or machine learning
  • Experience with domain randomization or procedural environment generation
  • Familiarity with ROS2 and modern robotics software stacks
  • Experience optimizing simulation performance or GPU-accelerated simulation
  • MS or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field
Why This Role Matters
Moonlake's vision depends on simulation systems that allow intelligent agents to learn, evaluate, and improve before operating in the physical world.
The quality of our world models, robotics systems, and AI infrastructure depends on simulation environments that are physically accurate, computationally efficient, and scalable.
As a Simulation Engineer, you'll build the core simulation infrastructure that powers the next generation of robotics and embodied AI.
We are committed to being an on-site, in-person team currently based in San Francisco.

Apply