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Senior Machine Learning Engineer, Neural Simulators

1 month, 3 weeks ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
Machine Learning MLOps Python PyTorch Reinforcement Learning
Apply Now
Path Robotics

Path Robotics

Path Robotics creates truly autonomous robots for manufacturing, eliminating the need for skilled welders or robot programmers and allowing humans to focus on creativity.

Automotive
51-250
Founded 2014
$71M raised
View All Jobs 33

Description

  • Build a learned world model of the welding process that predicts future system behavior under robot actions.
  • Develop multimodal neural simulators using inputs such as 3D scans, video, thermal data, and electrical measurements.
  • Design, train, and evaluate large-scale generative or dynamics models for long-horizon rollouts.
  • Collaborate with reinforcement learning engineers to integrate the simulator into RL training and evaluation pipelines.
  • Run hypothesis-driven experiments and ablation studies alongside production development.
  • 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.
  • Own pieces of the stack when needed and contribute across research and production work streams.

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.
  • Comfort training large models from scratch and working with the tooling and infrastructure needed to scale experiments.
  • Strong software engineering background with solid Python skills.
  • Experience with frameworks such as PyTorch or JAX.
  • Comfort working with messy, real-world data and imperfect ground truth.
  • Ability to model complex physical systems from data and reason about failure modes.
  • Willingness to context-switch between research and practical production work as needed.
  • Prior welding experience is not required (nice to have not expected).

Benefits

  • Daily free lunch.
  • Flexible PTO.
  • Comprehensive medical, dental, and vision coverage.
  • 6 weeks of 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.
  • Remote work option or on-site work at the Columbus, Ohio headquarters.

Interested in this position?

Apply directly on the company website

Apply Now

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