ML Engineer – Manipulation

Job not on LinkedIn

🕒 June 30

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Diligent Robotics

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2017

⚕️ Healthcare Insurance

🤖 Artificial Intelligence

💰 $30M Series B on 2022-04

Healthcare Insurance • Artificial Intelligence • Robotics

Diligent Robotics is a company that pioneers in integrating robotics into healthcare settings to improve efficiency and patient care. Their flagship robot, Moxi, assists hospital staff by fetching medications, labs, and supplies, significantly reducing the time healthcare professionals spend on non-clinical tasks. Diligent Robotics focuses on enhancing clinical workflows, addressing staff shortages, and ensuring better patient experiences through their innovative robotic solutions.

📋 Description

• Develop learning-based manipulation models for end to end sensor-driven interaction (e.g., reaching, motion generation, and execution in dynamic environments). • Build and maintain manipulation training pipelines: dataset creation from robot logs/teleop, action representations, augmentation, and distributed training. • Design evaluation metrics and regression tests that quantify manipulation reliability, recovery behavior, and safety in real environments. • Develop sim-to-real workflows for manipulation learning, including simulation environments, domain randomization, and failure-mode testing. • Optimize and distill models for edge deployment; benchmark latency, memory use, and stability on target hardware. • Partner with the AI platform team to integrate policies with control and safety systems, and validate end-to-end performance on robots. • Analyze field performance, identify dominant failure modes, and drive iterative improvements through data collection and targeted retraining.

🎯 Requirements

• Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD a plus). • 3+ years of experience applying ML to robotics manipulation, visuomotor control, or sequential to sequence models. • Strong proficiency in PyTorch and experience building reliable training/evaluation pipelines. • Strong software engineering skills in Python; ability to collaborate across ML and robotics teams.