Autonomous Machines

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,100,000; Full time

Job summary

Infosys in Bengaluru seeks a robotics research scientist to design SLAM, VLN, and VLA systems for autonomous robots across indoor and outdoor environments. You will develop perception pipelines, integrate ROS/ROS 2, and work with simulators like Gazebo and Isaac Sim, collaborating with AI and software teams to advance perception, planning, and control.

The role requires a PhD in robotics and a strong publication record, with experience deploying autonomous systems on real-world robotic

Qualifications

• PhD in robotics or related field with substantial publications.
• Publications in Tier-1 conferences and Q1 journals, patents, or significant project contributions.
• Experience deploying autonomous systems on real-world robotic platforms.

Responsibilities

• Design and develop SLAM algorithms for localization and mapping in varied environments.
• Research, implement, and evaluate VLN models for instruction-guided navigation.
• Develop VLA models enabling robots to perceive, reason, and manipulate tasks.
• Build autonomous navigation solutions with planning, control, and trajectory optimization.

Skills

Robotics

Perception pipelines

Python

PyTorch/TensorFlow

Reinforcement learning

ROS/ROS 2

Computer vision

Sensor fusion

Simulation

Education

PhD in robotics

Tools

ROS/ROS 2

Isaac Sim

Gazebo

MuJoCo

Omniverse

Job description

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 dynamic 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.

Additional Skills Aligned with This Role

• 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
• Field Robotics

Preferred Qualifications

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.