Senior Machine Learning Engineer (Reinforcement Learning/World Model)
Core
Develop neural world models and reinforcement learning algorithms to optimize welding processes and enable robots to learn in complex manufacturing environments.
Role type
Senior IC machine learning engineer (reinforcement learning & world models)
Builds
Neural welding simulators, RL policies, and synthetic data workflows for manufacturing robots
Domain
Robotics, manufacturing, applied physics, generative modeling
Deliverable
production ML models
Required skills
Reinforcement learning, neural world models, generative modeling, simulation environments, Python, deep learning frameworks, probability and statistics, production ML deployment
Preferred skills
Multimodal modeling, video prediction, latent dynamics, offline RL, constrained RL, uncertainty quantification
Technologies
PyTorch, TensorFlow, MuJoCo, Isaac Gym
Responsibilities
Build action-conditioned world models predicting welding process evolution; Develop RL approaches for optimizing welding decisions; Train and evaluate policies using learned models and real-world data; Translate research prototypes into dependable training and deployment systems
Seniority
Senior, hands-on IC
