Key Responsibilities:

- Design and develop Simultaneous Localization and Mapping SLAM algorithms for robust localization and mapping in indoor and outdoor environments
- Research implement and evaluate Vision Language Navigation VLN models for instruction guided autonomous navigation
- Develop and deploy Vision Language Action VLA models enabling robots to perceive reason and execute complex manipulation tasks
- Build autonomous navigation solutions using path planning motion planning obstacle avoidance and trajectory optimization techniques
- Work with robotic platforms including wheeled robots UGVs UAVs mobile manipulators and drone based manipulation systems
- Develop kinematic and energetic models including forward kinematics inverse kinematics motion control and whole body planning for robotic manipulators
- Integrate and optimize robotic software using ROS ROS 2 sensor fusion frameworks and distributed robotic architectures
- Create high fidelity simulation environments using Isaac Sim Gazebo Omniverse AirSim MuJoCo or similar simulators for development and validation
- Implement perception pipelines leveraging computer vision visual foundation models multimodal AI and sensor fusion across cameras LiDARs IMUs GPS and depth sensors
- Utilize the NVIDIA Physical AI ecosystem including Isaac Lab Isaac Sim Isaac ROS Cosmos Jetson and Omniverse for robot learning and deployment




- Develop AI driven robotic solutions using Python deep learning frameworks PyTorch TensorFlow and reinforcement learning techniques
- Evaluate robotic systems using simulation and real world benchmarks focusing on robustness safety scalability and deployment readiness

Technical Requirements:

- Embodied AI and Autonomous Agents Semantic Mapping and Scene Understanding 3D Computer Vision and Point Cloud Processing Grasp Planning and Manipulation Multi Robot Coordination and Swarm Robotics Model Predictive Control MPC Autonomous Exploration and Frontier Planning Navigation using Vision Foundation Models CLIP DINOv2 SigLIP Digital Twins and Sim to Real Transfer Safety Critical Autonomous Systems Edge AI deployment on NVIDIA Jetson platforms Warehouse Automation Industrial Robotics and Field Robotics

Additional Responsibilities:

- Essential Qualification Master s in Robotics Computer Science AI Machine Learning Electrical Engineering or related field
- Desired Qualification PhD in robotics field
- Publications in Tier 1 conferences and Q1 journals patents or significant project contributions in robotics autonomous systems embodied AI or computer vision
- Experience deploying autonomous systems on real world robotic platforms

Preferred Skills:

Technology->AI-Data science->Computer Vision

📌 Autonomous Machines - ARC (India)
🏢 Infosys
📍 India