Path Robotics

Senior Machine Learning Engineer, Neural Simulators

Vaga remota de Machine Learning Engineer com fit claro de localização do candidato.

Publicada13 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

Locais aceitos para candidatos

Estados Unidos

Resumo da vaga

Conteúdo da vaga extraído em seções para revisão mais rápida.

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.

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.

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.

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!

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