Senior Machine Learning Engineer Reinforcement Learning World Model

Skills

About the Role

You will develop learned world models and reinforcement-learning systems for welding robotics. You will model visual and physical welding dynamics, train and evaluate policies, quantify uncertainty, validate predictions with real-world data, diagnose unsafe or unstable behavior, and turn research work into dependable training, evaluation, inference, and deployment systems.

Requirements

• Master’s or PhD in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience.
• Experience developing and deploying reinforcement-learning algorithms on real-world systems.
• Proficiency in Python and deep-learning frameworks such as PyTorch or TensorFlow.
• Experience with simulation environments such as MuJoCo or Isaac Gym.
• Understanding of probability, statistics, and optimization.
• Experience training and deploying machine-learning models in production systems.

Responsibilities

• Build action-conditioned world models for welding-process dynamics.
• Model inputs, system state, physical dynamics, and weld quality.
• Develop multimodal models using video, 3D scans, thermal measurements, electrical signals, robot state, and process parameters.
• Improve rollout accuracy, physical plausibility, temporal consistency, and computational efficiency.
• Quantify model uncertainty and validate predictions against real-world welding data.
• Integrate learned models into reinforcement learning, planning, process optimization, evaluation, and synthetic-data workflows.
• Develop reinforcement-learning approaches for optimizing welding decisions and outcomes.
• Define state, observation, action, and reward representations.
• Train and evaluate policies using learned models, simulation, offline data, and controlled real-world experiments.
• Diagnose reward exploitation, unsafe behavior, policy instability, and model exploitation.
• Translate research prototypes into dependable training, evaluation, and deployment systems.

Benefits

• Daily free lunch
• Flexible PTO
• Medical, dental, and vision coverage
• 6 weeks of fully paid parental leave, plus an additional 6–8 weeks for birthing parents
• 401(k) retirement plan through Empower
• Employee referral bonuses