Physical AI and robotics projects

Your robotics and spatial computing expertise shapes how AI interacts with physical environments. Join the talent pool for upcoming projects!

Join the talent pool

What are physical AI projects?

Physical AI, or embodied AI, are systems that perceive, navigate, and interact with the real world. These can't be built on text and image training alone.

Through Mindrift, contributors with robotics and computer vision expertise annotate egocentric video, label 3D point clouds, and evaluate robotic action sequences to help build AI that operates safely in physical environments.

Gartner named physical AI a top strategic technology trend for 2026, and demand for skilled contributors is accelerating.

What you get

Physical AI projects on Mindrift offer competitive rates matching the specialized expertise required. Projects are fully remote and flexible – contributors set their own schedule and participate at their own pace.

Competitive per-task rates

Hands-on AI experience

Flexible remote project

Global community

Types of physical AI tasks

Tasks vary between projects, but generally center around annotating real-world spatial data, evaluating AI-generated action plans, and providing the feedback that teaches AI to operate in physical environments.

Egocentric data collection

Wear a head- or wrist-mounted camera and perform object manipulations following the task brief. You return clean first-person footage ready for model training.

RGB-D data collection

Teleoperation data collection

Who can join physical AI projects?

Physical AI projects require specialized expertise in spatial computing, robotics, or computer vision. These are advanced tasks for professionals who understand how machines perceive and interact with the three-dimensional world.

Robotics engineers

Professionals with experience in robotic manipulation, motion planning, or autonomous systems. You understand kinematics, grasp planning, and the gap between simulated and real-world performance.

Computer vision and 3D annotation specialists

Experts experienced with point cloud annotation, depth estimation, semantic segmentation, or volumetric labeling. You have worked with LiDAR, stereo vision, or structured-light sensor data.

Spatial computing and AR/VR professionals

Developers and researchers working in augmented reality, virtual reality, or spatial computing. You have hands-on experience with 3D scene understanding, SLAM, and real-time environment mapping.

Physical AI projects are in active development. Join the talent pool now and be among the first contributors notified when projects launch.

There is no commitment until you accept a project. Joining the pool takes minutes and ensures your profile is ready when opportunities matching your skills become available.

How to get started

1. Apply

Submit your CV and indicate your robotics, CV, or spatial computing expertise

2. Qualify

Complete a domain-specific assessment when projects launch

3. Onboard

Get platform access and project guidelines walkthrough.

4. Earn

Start completing tasks at your own pace

Why physical AI matters now

Physical AI represents the next frontier of AI training. Models that interact with the real world safely and reliably are still in early stages. The training data challenge for physical AI is fundamentally different: it requires 3D spatial understanding, temporal reasoning about actions and consequences, and the kind of real-world physics intuition that only domain experts bring.

Mindrift is building the contributor network for this emerging field. Over 20,000 experts worldwide have already joined the Mindrift community across coding, STEM, writing, and other domains, backed by Toloka AI. Physical AI is the next chapter. Learn more about AI trends shaping 2026 or explore all current openings .