Research Engineer, Post-training & Deployment
Core
Improving Skild foundation models and deploying them onto robots in the field to ensure safe, efficient, and robust robot behavior in real-world environments.
Role type
Research Engineer (Post-training & Deployment)
Builds
Production ML models for robotic manipulation and full-stack software/hardware deployments for customer sites
Domain
Robotics, Deep Learning, Computer Vision
Deliverable
production ML models
Required skills
Python, deep learning libraries (PyTorch, TensorFlow, JAX), computer vision, reinforcement learning, imitation learning, large-scale model training, ROS/ROS2
Preferred skills
LLMs for development acceleration, customer deployment experience
Technologies
PyTorch, TensorFlow, JAX, ROS, ROS2
Responsibilities
Research, post-train and evaluate large deep learning models for robotic manipulation tasks; Develop frameworks to continuously improve robot behaviors; Collaborate with product teams to align technical requirements for on-site deployments; Own scenario setup and data collection methodologies for unique customer use-cases; Work with robotics teams to maintain deployment-ready robots and execute full-stack software and hardware deployments; Build robust testing and evaluation pipelines for tracking model improvements and corner cases
Seniority
Individual Contributor
