Job Title: Physical AI Engineer

Company: Muks Robotics AI Pvt. Ltd.

Website: https://muksrobotics.com/

Location: Baner, Pune

Experience: 2-3 years

About the Role :

As a Physical AI Engineer, you will be responsible for integrating LLMs, VLMs, and VLA models directly onto our humanoid robots, enabling real-time perception, reasoning, control, and manipulation. This is a highly hands-on role involving robots, sensors, actuators, embedded compute, and full-stack AI pipelines.

Key Responsibilities:

1.   AI Integration & Deployment

●    Deploy and adapt LLM/VLM/VLA models on edge platforms like Jetson Orin, Nvidia GPUs and ARM-based hardware.

●    Connect AI outputs to robot software pipelines for task execution and interaction.

●    Optimize models for speed, reliability, and on-device inference.

2.   Perception & Sensing

●    Build vision and multimodal perception modules for scene understanding, grounding, and pose estimation.

●    Combine data from cameras, force/torque sensors, tactile sensors, and robot joints.

●    Implement lightweight memory/continuity modules for stable task performance.

3.   Control & Execution

●    Link high-level AI decisions with motion controllers for manipulation, locomotion, and coordinated actions.

●    Validate behaviors generated by AI models and refine parameters for smooth, safe operation.

●    Handle timing, safety checks, and real-time control loops.

4.   Experimentation & Hardware Work

●    Run hands-on tests on humanoid robots for tasks like pick/place, handovers, and tool usage.

●    Work on low-latency communication between hardware components (ROS/ROS2, CAN, serial protocols).

●    Diagnose issues across sensors, actuators, drivers, and communication interfaces.

●    Set up logging, telemetry, and evaluation tools for systematic testing.

5.   Data Workflows

●    Capture multimodal datasets from real robot trials.

●    Build simple pipelines for preprocessing, organization, and annotation.

●    Support demonstration-based learning and teleoperation data collection.

6.   Safety & Reliability

●    Implement guardrails, fallback behaviors, and monitoring systems to ensure safe AI-driven actions.

Required Qualification & Skills:

●    Bachelor’s or a Master’s degree in Computer Science, AI/ML or related field.

●    Strong experience integrating LLMs/VLMs/VLA models into robotic systems (grounding, reasoning, action planning).

●    Solid foundation in deep learning tools: PyTorch, ONNX, TensorRT.

●    Experience with ROS/ROS2 and real-time robot bring-up.

●    Proficiency in Python and C++.

●    Hands-on experience with robotics platforms: manipulators, grippers, mobile bases, or humanoids.

●    Good understanding of kinematics, dynamics, control loops, and robotic safety.

●    Experience working with Jetson/embedded inference systems.

Preferred (Not mandatory):

●    Experience with generalist robotic models (RT-X, GR00T, OpenVLA, Octo, VIDIA-like architectures, or internal equivalents).

●    Experience building teleoperation, imitation learning, or demonstration-based skill pipelines.

●    Knowledge of SLAM, 3D reconstruction, depth fusion, or scene graph generation.

●    Familiarity with memory systems, vector databases, or trajectory libraries for robotic decision-making.

●    Exposure to whole-body control: MPC, QP solvers, whole-body IK.

●    Contributions to open-source robotics or AI frameworks.

What We Offer:

● Opportunity to work on futuristic robotics technologies.

● A collaborative and innovative work environment.

● Growth opportunities in a rapidly expanding tech company.

● Competitive salary and performance-based incentives.