Trainer – Physical AI & RoboticsNVIDIA Isaac | ROS 2 | Isaac Sim | LeRobot | Robotics AI

Organization: AI5 Academy
Role Type: Part-Time / Freelance Trainer
Mode: Live Online
Schedule: Weekday / Weekend batches depending on availability
Location: Remote

Role Overview

AI5 Academy is looking for a hands-on Physical AI & Robotics Trainer to teach learners how modern AI models connect with robots and physical systems.

The trainer should be comfortable teaching both robotics foundations and current AI-driven robotics workflows using NVIDIA Isaac, ROS 2, simulation environments, computer vision and LeRobot.

This is a practical teaching role. We are particularly interested in candidates who have built, simulated, programmed or researched robotic systems rather than candidates with only theoretical knowledge.

What You Will Teach

The trainer should be able to cover most of the following areas:

Physical AI & Robotics Foundations

- Physical AI and embodied AI concepts
- Robot architecture: sensors, actuators, controllers and compute
- Autonomous and semi-autonomous robotic systems
- Perception → reasoning → planning → action workflow
- AI models in real-world robotic systems

ROS 2

- ROS 2 architecture
- Nodes, topics, services and actions
- Publishers and subscribers
- Packages and workspaces
- TF and coordinate frames
- URDF/Xacro robot models
- Sensor integration
- Navigation and robot control
- Debugging and visualization with ROS tools

NVIDIA Isaac

- NVIDIA Isaac ecosystem
- Isaac Sim
- Robot simulation
- Synthetic data generation
- Camera, LiDAR and sensor simulation
- Perception workflows
- NVIDIA Isaac ROS
- GPU-accelerated robotics
- Simulation-to-real concepts

Robot Perception & Computer Vision

- Camera-based perception
- Object detection and tracking
- Depth estimation
- Pose estimation
- Sensor data processing




- Vision-based robotic tasks

LeRobot & Robot Learning

- Hugging Face LeRobot
- Robot datasets
- Data collection
- Imitation learning concepts
- Training robot policies
- Vision-language-action concepts
- Using pretrained models for robotics
- Running and evaluating learned robot behaviours

Autonomous Robotics

- Mapping and localization
- SLAM concepts
- Path planning
- Navigation
- Obstacle avoidance
- Manipulation fundamentals
- Robotic arms and mobile robots
- Human-robot interaction

Generative AI & Robotics

- LLMs and multimodal models for robotics
- Vision-language models
- Vision-language-action models
- Natural-language robot commands
- AI agents connected with robotic systems
- Safety and human supervision

Practical Projects

The trainer should be able to guide learners through projects such as:

- Building a ROS 2 robotic workflow
- Creating and controlling a robot inside Isaac Sim
- Simulating sensors and environments
- Vision-based object detection for a robot
- Autonomous navigation project
- Robotic arm pick-and-place simulation
- Collecting robot demonstration data
- Training or testing a robot policy using LeRobot
- Natural-language-controlled robotics prototype
- Capstone Physical AI project

Required Skills

Candidates should have practical knowledge of:

- ROS 2
- Python
- Linux / Ubuntu
- Robotics fundamentals
- Robot simulation
- Computer vision
- Sensors and actuators
- Git/GitHub

Solid preference will be given to candidates with experience in:





- NVIDIA Isaac Sim
- Isaac ROS
- Hugging Face LeRobot
- PyTorch
- OpenCV
- SLAM/navigation
- Robotic arms or mobile robots
- Reinforcement or imitation learning
- NVIDIA Jetson
- Real-world robot deployment

Who Can Apply

Suitable candidates may come from backgrounds such as:

- Robotics Engineer
- Autonomous Systems Engineer
- Robotics AI Engineer
- ROS/ROS 2 Developer
- Computer Vision Engineer working with robotics
- Robotics Researcher
- Mechatronics Engineer
- AI/ML Engineer with robotics experience
- University faculty/researchers working in robotics or embodied AI

Teaching Requirements

The trainer should be able to:

- Conduct live instructor-led online sessions
- Explain technical topics to learners from mixed backgrounds
- Demonstrate tools live rather than relying only on slides
- Create practical assignments and projects
- Review student projects and troubleshoot errors
- Keep course material aligned with current Physical AI and robotics tools
- Provide installation/setup guidance for required software
- Conduct an initial demo session before final onboarding

Preferred Experience

- 2+ years of relevant robotics/AI work, research or teaching experience preferred
- Previous training experience is an advantage but not mandatory
- Candidates with strong project portfolios may be considered even with limited formal teaching experience

Application

Please share:

- Updated CV
- LinkedIn profile
- GitHub/robotics project portfolio, if available
- ROS 2 experience
- NVIDIA Isaac/Isaac Sim experience
- LeRobot or robot-learning experience
- Hardware platforms previously used
- Teaching/training experience
- Available days and timings

AI5 Academy

Pay: ₹9,379.99 - ₹20,000.00 per month

Benefits:

- Flexible schedule

Work Location: Remote

📌 Trainer – Physical AI & Robotics (India)
🏢 AI5 Academy
📍 India