AI Researcher - Computer Vision

About the Role

As an AI Researcher for Computer Vision & Autonomous Robots at TCS, you’ll work on the frontier of applied artificial intelligence, where perception meets physical intelligence. This role is designed for bright, curious, and self-driven graduates who aspire to build the next generation of intelligent robotic systems - capable of seeing, reasoning, and acting autonomously in the physical world.

You will collaborate with interdisciplinary teams of researchers, data scientists, and roboticists to explore, prototype, and implement computer vision and machine learning algorithms that power autonomous robots, humanoids, and intelligent machines. From visual perception and SLAM to multimodal sensor fusion and reinforcement learning, you’ll be pushing the boundaries of what machines can perceive and do.

If you are passionate about AI, robotics, and human–machine collaboration and want to shape how intelligent systems interact with the world - this is your launchpad.

Key Responsibilities

AI Research & Experimentation

• Research, develop, and prototype novel algorithms in computer vision, deep learning, and autonomous systems.
• Work on topics such as object detection, pose estimation, scene understanding, 3D reconstruction, and sensor fusion.
• Contribute to building perception pipelines for autonomous mobile robots (AMRs), humanoids, and collaborative robotic systems.

Development & Implementation

• Design, train, and optimize deep neural networks using frameworks such as PyTorch or TensorFlow.
• Develop real-time perception and decision systems using ROS, OpenCV, and NVIDIA Jetson/Isaac SDKs.
• Implement algorithms for navigation, path planning, and control integration.

Collaboration & Innovation

• Partner with cross-functional teams in AI, robotics, and systems engineering to co-create innovative prototypes.
• Participate in TCS research initiatives, innovation challenges, and client-facing proof-of-concept demonstrations.
• Contribute to whitepapers, patents, and internal publications advancing TCS’s thought leadership in AI and robotics.

Continuous Learning & Experimentation

• Stay current with advances in AI, robotics, and multimodal learning from academia and industry.
• Experiment with new architectures (e.g., Vision Transformers, Diffusion Models, Agentic AI frameworks).
• Test and benchmark algorithms on physical robot platforms and simulation environments (e.g., Gazebo, Isaac Sim).

Required Qualifications & Skills

Educational Background:

• Bachelor’s or Master’s or Ph. D in Computer Science, Robotics, Electrical/Electronics Engineering, Mechatronics, or AI/ML from a recognized institution.
• Strong academic foundation in machine learning, image processing, linear algebra, and probability.

Technical Skills:

• Proficiency in Python and familiarity with frameworks such as PyTorch, TensorFlow, OpenCV, and ROS.
• Good understanding of deep learning architectures (CNNs, RNNs, Transformers).
• Exposure to robotics simulation environments (Gazebo, Isaac Sim, CARLA) or embedded systems (Jetson, Raspberry Pi).
• Familiarity with Linux, Git, and collaborative development workflows.

Soft Skills & Mindset:

• Passion for solving open-ended research problems and building working prototypes.
• Curiosity to explore and apply cutting-edge AI to physical systems.
• Strong analytical thinking and a problem-solving mindset.
• Collaborative attitude and eagerness to learn from interdisciplinary teams.

Preferred, but not mandatory:

• Internship or project experience in computer vision, autonomous navigation, or robotics research labs.
• Publications or participation in AI/robotics competitions (e.g., RoboCup, CVPR workshops, Kaggle, DARPA challenges).
• Exposure to edge AI optimization (TensorRT, ONNX) or reinforcement learning.