Job Title: Physical AI Engineer
Experience: 2 years
Location: Baner, Pune
Company: Muks Robotics AI Pvt. Ltd.
Employment Type: Full-time | On-site

About the Role:

We are looking for a Physical AI Engineer to work on next-generation autonomous and humanoid robotic systems. The role focuses on integrating AI models with physical robotic systems, enabling robots to perceive, reason, and interact with the real world.

The ideal candidate will have experience working with robotics, computer vision, and modern AI models such as LLMs or VLMs, and will contribute to building intelligent robotic capabilities from perception to action.

Key Responsibilities:

• Develop and integrate AI models (LLM / VLM / multimodal models) for robotic perception and decision-making
• Implement AI pipelines for perception, reasoning, planning, and robotic actions
• Work on vision-based understanding, scene interpretation, and robot interaction with the environment
• Optimize AI inference for edge deployment on robotic hardware such as NVIDIA Jetson or similar platforms
• Integrate AI models with robotics frameworks such as ROS / ROS2 Collaborate with robotics, embedded systems, and mechanical teams to deploy AI capabilities on robots
• Develop and test robot behaviors using sensor inputs such as cameras, IMUs, LiDAR, or microphones
• Run experiments, evaluate model performance, and improve real-world reliability of AI systems
• Maintain clean documentation, reproducible experiments, and high-quality code

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Robotics, or related field
• 2 years of experience working in AI, robotics, or autonomous systemsExperience with Python and C++ for AI or robotics development
• Strong experience with PyTorch or similar deep learning frameworks Familiarity with ROS / ROS2 and robot bring-up
• Understanding of robotics fundamentals (kinematics, perception, control basics)
• Experience deploying models using ONNX, TensorRT, or similar inference frameworksPrior proven experience with VLA is a plus
• Familiarity with computer vision, multimodal AI, or perception systems

Work Location: In person