AI Robotics Engineer

Location: Bangalore (on-site)

Type: Full-time

Experience: 0-2 years

Position Overview

We are seeking an AI Robotics Engineer to develop intelligent robotic systems using advanced simulation platforms and robot SDKs. You will create AI-powered robot behaviors, generate synthetic training data, and deploy solutions using high-level APIs.

Core Technical Requirements

AI & Machine Learning

- Knowledge of machine learning frameworks (TensorFlow, PyTorch)

- Computer vision expertise: object detection, SLAM, visual odometry

- Reinforcement learning implementation and training

- Deep learning model deployment on edge devices

- Natural language processing for human-robot interaction

- Model optimization and quantization techniques

Simulation Platforms

- NVIDIA Isaac Sim proficiency with Omniverse integration

- USD (Universal Scene Description) scene creation and management

- Physics simulation tuning with PhysX engine

- Synthetic data generation and domain randomization

- Multi-GPU simulation scaling and optimization

- Isaac Gym for RL training environments

Alternative Simulation Experience

- Gazebo, MuJoCo, PyBullet, or CoppeliaSim

- Unity ML-Agents or Unreal Engine robotics integration

- Custom simulation environment development

- Real-time physics simulation optimization

- Sensor simulation and noise modeling

Programming & Development

- Expert Python programming for AI/ML and robotics

- C++ for performance-critical applications and ROS integration

- ROS/ROS2 ecosystem: nodes, topics, services, actions

- Robot SDK integration (Boston Dynamics, Unitree, Universal Robots, etc.)

- Linux development environment proficiency

- Git version control and collaborative development

Computer Vision & Perception

- OpenCV for real-time image processing

- 3D point cloud processing and analysis

- Camera calibration and coordinate transformations

- Object tracking and recognition algorithms

- Stereo vision and depth estimation

- Multi-sensor fusion techniques

Advanced Simulation Skills

- Sim-to-real transfer techniques and validation

- Procedural environment generation

- Multi-robot swarm simulation

- Performance profiling and optimization

- Distributed simulation across cloud infrastructure

- Realistic sensor modeling and calibration

Technical Challenges You'll Solve

- Design RL training environments for complex robot behaviors

- Implement sim-to-real transfer with minimal performance degradation

- Create photorealistic simulations for computer vision training

- Optimize simulation performance for real-time robot testing

- Build scalable synthetic data generation pipelines

- Develop multi-modal sensor fusion algorithms

Required Experience

- Built and deployed AI models on physical robots

- Created simulation environments from scratch

- Implemented computer vision systems for robotics applications

- Worked with robot manufacturer SDKs and APIs

- Developed real-time perception and decision-making systems

- Experience with cloud-based simulation platforms

Tech Stack

AI/ML: PyTorch, TensorFlow, OpenCV, scikit-learn

Simulation: NVIDIA Isaac Sim, Gazebo, MuJoCo

Robotics: ROS2, robot manufacturer SDKs

Cloud: AWS RoboMaker, Docker, Kubernetes

Languages: Python, C++, CUDA

Graphics: USD, Omniverse, Unity/Unreal

What We Offer

- Access to cutting-edge simulation hardware and software

- Opportunity to work with latest robotics platforms

- Collaborative environment with AI and robotics experts

- Competitive salary and equity package