Machine Learning Engineer (Robotics/ Physical AI)

Job Title: Machine Learning Engineer (Robotics/ Physical AI) Company: PeopleGene Job Category: Machine Learning Roles & Responsibilities: About the role: * Build training data to operate on physical robotic platforms. * Own the full machine learning lifecycle—from data collection and custom architecture design to edge deployment, simulation\-to\-real (sim\-to\-real) transfer, and continuous hardware optimization. * Design, train, and evaluate deep learning, computer vision, and multimodal models (e.g., Vision\-Language\-Action or VLA systems) for robotic perception, reasoning, and manipulation. * Apply synthetic data, domain randomization, imitation learning, and reinforcement learning within simulation environments before transferring policies to physical robots. * Optimize, quantize, and compile ML models to run with low latency on edge compute hardware, sensors, and embedded robotic platforms. * Build and maintain scalable data ingestion, labeling, automated testing, and MLOps/monitoring pipelines for real\-world operational data. * Work side\-by\-side with mechanical, electrical, controls, and software engineers to integrate AI models into safe, reliable physical machines. Work Location: Bengaluru, Karnataka, India Availability: Full time

* Strong ML fundamentals, computer vision, coding skills, and Claude Code usage * Prior experience on perception models, multimodal datasets, and data pipelines for robotics. * Strong experience in SLAM, computer vision, quick prototyping research papers, model optimization and deployment, Azure ML, claude code. * Good understanding of SLAM, 3D reconstruction, real2sim, human exoskeletons and similar problems. * Preference for hardware or full stack engineering; VLAs or Robotics learning. * Prior 2\-0 years of experience in Machine learning at high growth ventures. * Advanced proficiency in Python and familiarity with Linux/Unix development environments. * Practical background in computer vision, sensor fusion (cameras, LiDAR, IMUs), SLAM, or robot control/policies (imitation learning and reinforcement learning). * Experience with edge inference optimization (ONNX, TensorRT), containerization (Docker, Kubernetes), Git, and CI/CD workflows. * Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical/Mechanical Engineering, or a related technical field. Key Skills: Machine Learning, Python, Computer Vision Salary: Not disclosed