Upsurge Labs

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&aposll 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 Show more Show less