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ML Engineer, Manipulation

3 weeks, 3 days ago
United States
Full-time
Mid Level
Machine Learning Engineer
Software Development
Machine Learning Python PyTorch
Apply Now
Diligent Robotics

Diligent Robotics

Diligent Robotics builds robots like Moxi that assist hospital staff with routine activities so they can focus on caring for patients. The company's mission is to make technical advances towards robots and humans working together side by side, with an ...

Health Care Providers & Services
51-250
$72M raised
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Description

  • Develop end-to-end, sensor-driven manipulation models for reaching, motion generation, and execution.
  • Build and maintain manipulation training pipelines using robot logs and teleoperation data, including action representations, augmentation, and distributed training.
  • Design evaluation metrics and regression tests for manipulation reliability, recovery behavior, and safety.
  • Develop sim-to-real workflows, including simulation environments, domain randomization, and failure-mode testing.
  • Optimize and distill models for edge deployment while benchmarking latency, memory usage, and stability.
  • Integrate manipulation policies with control and safety systems in partnership with the AI platform team.
  • Validate end-to-end performance on robots and analyze field results to identify failure modes.
  • Drive improvements through targeted data collection and retraining.

Requirements

  • Bachelor’s or master’s degree in Robotics, Computer Science, Electrical Engineering, or a related field; PhD preferred.
  • 3+ years of experience applying machine learning to robotic manipulation, visuomotor control, or sequence-to-sequence models.
  • Strong proficiency with PyTorch and reliable training and evaluation pipelines.
  • Strong Python software engineering skills and ability to collaborate across ML and robotics teams.
  • Experience with Vision-Language-Action models, behavior cloning, transformer policies, or diffusion policies preferred.
  • Experience with sim-to-real manipulation training using Isaac Sim, MuJoCo, or similar tools preferred.
  • Experience deploying models to edge hardware using ONNX, TensorRT, quantization, or performance profiling preferred.
  • Familiarity with safety-critical robotics integration and fallback or recovery behaviors preferred.

Interested in this position?

Apply directly on the company website

Apply Now

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