Senior Machine Learning Engineer, Neural Simulators

What You’ll Do

• 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.

Who You Are

• 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.
• 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.

A Note on Background

We do not expect prior welding experience. We do expect comfort modeling complex physical systems from data, reasoning about failure modes, and iterating toward accuracy under real-world constraints.

Why This Role

• You’ll help define the core learning infrastructure that underpins our robotic systems.
• You’ll have space to pursue research tracks that run in parallel with production development.
• You’ll work on problems where success is measurable in the physical world - not just benchmarks.
• You’ll join a team that values depth, ownership, and adaptability over narrow specialization.

Why You’ll Love Working Here

• 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!