Research Engineer, Post-training & Deployment

Roles and Responsibilities:\n- Research, post-train and evaluate large deep learning models for robotic manipulation tasks.\n- Develop frameworks to continuously improve robot behaviors.\n- Collaborate closely with our product teams to source and iterate on customer requirements to ensure technical alignment for on-site deployments.\n- Own scenario setup and data collection methodologies, managing the operational lifecycle for unique customer use-cases.\n- Work with our robotics teams to maintain and ensure robots are deployment-ready and execute full-stack software and hardware deployments at customer sites.\n- Build robust testing and evaluation pipelines for tracking model improvements and corner cases.\n\n### Preferred Qualifications:\n- BS, MS or PhD degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.\n- Proficiency in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.\n- Deep technical knowledge in computer vision and deep learning for robotics, including reinforcement and imitation learning.\n- Prior experience working with large-scale model training.\n- Prior experience developing and deploying ML models or software on real robots.\n- Prior experience with ROS/ROS2 or other robotics middleware platforms.\n- Bonus if you have experience working with customers and deploying real-world robotics applications.\n- Bonus if you have experience leveraging LLMs to accelerate development and solve complex engineering problems.