Senior Machine Learning Engineer

Responsibilities

The Senior Machine Learning Engineer will research, prototype, and develop AI-driven models for robotic manipulation, grasping, and object interaction, designing and optimizing Classical ML / deep learning and reinforcement learning (RL) models for robotic control and decision-making. They will develop simulation-driven ML pipelines, integrating synthetic data, real-world sensor data, and reinforcement learning, and work with different learning models, including Large Language Models (LLMs), transformer-based architectures, and generative AI to enhance robotic intelligence. The role involves collaborating with robotics engineers, software developers, and mechatronics teams to integrate ML models into real-world robotic systems, designing and implementing scalable ML frameworks for real-time robotics applications, conducting model evaluation, benchmarking, and performance tuning, and developing and maintaining data pipelines, including sensor data collection, annotation, and preprocessing for AI model training. Furthermore, the engineer will experiment with foundation models and generative AI for robotics applications, working with physics-based simulators (Isaac Sim, Mujoco, PyBullet, Gazebo, DRAKE) to train and validate ML models.