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Embodied Ai Jobs in California (NOW HIRING)

General Motors

Senior Manager, Embodied AI

Sunnyvale, CA · On-site

$296K - $453K/yr

We are seeking an experienced and technically strong Senior Engineering Manager - AI/ML Engineering for the Data Foundations organization of Embodied AI. This role emphasizes day-to-day people ...

General Motors

Senior Manager, Embodied AI

Sunnyvale, CA · On-site

$296K - $453K/yr

We are seeking an experienced and technically strong Senior Engineering Manager - AI/ML Engineering for the Data Foundations organization of Embodied AI. This role emphasizes day-to-day people ...

General Motors

Senior Manager, Embodied AI

Sunnyvale, CA · On-site +1

$296K - $453K/yr

We areseekingan experienced and technically strong SeniorEngineering Manager - AI/MLEngineeringforthe Data Foundations organization of Embodied AI. This role emphasizes daytodaypeoplemanagement ...

Intuitive

Staff AI/ML Architect, Embodied AI

Sunnyvale, CA · On-site

$74.75 - $96.25/hr

Foundation-model adaptation and fine-tuning for embodied robotics tasks. * Experience delivering AI/ML in a real-time, safety-critical domain. * Imitation learning, DAgger, and/or reinforcement ...

Intuitive

Staff AI/ML Architect, Embodied AI

Sunnyvale, CA

$74.75 - $96.25/hr

Foundation-model adaptation and fine-tuning for embodied robotics tasks. * Experience delivering AI/ML in a real-time, safety-critical domain. * Imitation learning, DAgger, and/or reinforcement ...

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Embodied Ai information

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.

What are popular job titles related to Embodied Ai jobs in California?

For Embodied Ai jobs in California, the most frequently searched job titles are:

What job categories do people searching Embodied Ai jobs in California look for?

The top searched job categories for Embodied Ai jobs in California are:

What cities in California are hiring for Embodied Ai jobs?

Cities in California with the most Embodied Ai job openings:

Embodied Ai jobs near you
Infographic showing various Embodied Ai job openings in California as of August 2026, with employment types broken down into 72% Full Time, 23% Part Time, and 5% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Embodied AI Lead / Robot Brain Lead

Faraday Future

El Segundo, CA • On-site

$109K - $143K/yr

Full-time

Re-posted yesterday

Job description

Job Summary:
Faraday Future is a California-based technology company focused on the design, engineering, and development of intelligent, connected electric vehicles and related artificial intelligence–enabled technologies. As the Embodied AI Lead or Robot Brain Lead, you will own the overall Embodied AI architecture for the platform, guiding a small team to turn cutting-edge research into robust, production-ready capabilities.
Responsibilities:
• Design the overall Robot Brain architecture: + System 2: VLM/LLM/VLA for semantic understanding and task planning. + System 1: visuomotor control for locomotion and manipulation. + World model integration for rollouts and safety.
• Define a short-term and long-term technical roadmap balancing innovation and deliverables.
• Make key decisions on model families and training strategies: + E2E visuomotor, diffusion policies, transformer policies, VLA-based approaches, RL/BC hybrids.
• Lead the implementation and deployment of the first production version of the Robot Brain on at least one robot platform.
• Drive iterative improvements as we expand tasks and sites.
• Collaborate with Control & Robotics: + Co-design skills (navigate, pick, place, open, inspect, etc.). + Ensure Brain outputs are physically feasible and robust.
• Collaborate with Agent & Applications: + Align Brain capabilities with real workflows and job definitions.
• Collaborate with Platform & Data: + Define training data schemas and logging requirements. + Build end-to-end training and deployment pipelines.
• Define evaluation protocols for the Brain: + Task success, robustness, long-horizon stability, safety incident metrics.
• Work with World Model & Safety teams to incorporate predictive safety and scenario-based testing.
• Ensure the Brain is observable, debuggable, and improvable in production.
• Hire, mentor, and lead a small Embodied AI team (3–6 engineers/researchers initially).
• Establish high standards for engineering quality, experimentation, and documentation.
• Represent the Embodied AI function in technical and cross-functional planning (product, hardware, operations).
Qualifications:
Required:
• Bachelor's or higher in CS, Robotics, EE, or related field.
• 5+ years in ML / robotics, including 2+ years in a lead / tech lead role.
• Deep experience in at least two of: Proven track record deploying ML models on real robotic hardware, not just simulation.
• Strong coding skills in Python and experience with PyTorch or JAX, multi-GPU training.
• Strong written and verbal communication; able to write clear design docs and align stakeholders.
Preferred:
• PhD or equivalent industry research experience in Robotics, AI, Machine Learning, or a related field.
• Hands-on experience with foundation models for robotics, such as VLMs, VLAs, or multimodal LLM-based agents applied to real-world embodied tasks.
• Experience building or scaling robot learning systems in production, including data collection at scale, sim-to-real transfer, and continuous learning loops.
Company:
Faraday Future develops humanoid and quadruped robots for education, security, and commercial use. Founded in 2014, the company is headquartered in El Segundo, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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