Senior Machine Learning Engineer, Neural Simulators

Responsibilities

• Build a learned world model of the welding process that predicts future system behavior under robot actions
• Develop multimodal neural simulators incorporating signals such as 3D scans, video, thermal data, and electrical measurements
• Design, train, and evaluate large-scale generative or dynamics models capable of long-horizon rollouts
• Collaborate with reinforcement learning engineers by integrating the neural simulator into RL pipelines
• Run research tracks in parallel with production development, including hypothesis-driven experimentation
• Partner with data and MLOps teams to support scalable training, evaluation, and deployment
• Translate research prototypes into robust, maintainable production code
• Validate simulator performance against real-world robotic welding data and support sim-to-real transfer

Requirements

• Experience building and deploying ML systems for robotics or complex physical processes
• Hands-on experience with world models, learned simulators, video generation, 3D modeling, or dynamics prediction
• Experience training large models from scratch and working with scaling infrastructure
• Proficiency in Python
• Experience with PyTorch or JAX

Benefits

• Daily free lunch
• Flexible PTO
• Comprehensive medical, dental, and vision coverage
• 6 weeks fully paid parental leave (12–14 weeks total for birthing parents)
• 401(k) retirement plan
• Generous employee referral bonuses

About the Company

At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries.