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 (e.g., video prediction, latent world models, 3D or spatiotemporal representations) capable of long-horizon rollouts.
- Collaborate with reinforcement learning engineers by integrating the neural simulator into RL pipelines for policy training and evaluation.
- Run research tracks in parallel with production development, including hypothesis-driven experimentation and ablation.
- Partner closely with data and MLOps teams to support scalable training, evaluation, and deployment - while remaining comfortable owning pieces of the stack when needed.
- Translate research prototypes into robust, maintainable production code when they prove valuable.
- 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 other complex physical processes in real-world settings.
- Hands-on experience with world models, learned simulators, video generation, 3D modeling, or dynamics prediction.
- Comfortable training large models from scratch and working with the tooling and infrastructure required to scale experiments.
- Enjoy working with messy, real-world data and are pragmatic about imperfect ground truth.
- Strong software engineer with solid Python skills and experience in frameworks such as PyTorch or JAX.
Nice to Have
- You are excited by a role that blends research depth with practical impact, and you’re willing to context-switch when the team needs it.
Benefits
- Daily free lunch to keep you fueled and connected with the team
- Flexible PTO so you can take the time you need, when you need it
- Comprehensive medical, dental, and vision coverage
- 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
- 401(k) retirement plan through Empower
- Generous employee referral bonuses—help us grow our team!
Work Arrangement
Hybrid
Additional Information
- If you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact HR@path-robotics.co. We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. We will respond to your request within 48 hours.
