Position Details
About this role
This role involves leading the development of advanced robot learning models, including reinforcement and imitation learning, deploying large-scale models, and creating simulation environments for validation in autonomous robotics.
Key Responsibilities
- Lead robot learning model development
- Design simulation environments
- Optimize deployment of ML models
- Identify system performance bottlenecks
- Collaborate on building reusable software frameworks
Technical Overview
The technical environment includes PyTorch, DeepSpeed, ROS/ROS2, and simulation tools, focusing on large-scale ML models, reinforcement learning, and robotics system integration.
Ideal Candidate
The ideal candidate is a highly experienced machine learning engineer with over 8 years in robot learning research or engineering. They should have expertise in reinforcement and imitation learning, proficiency with PyTorch, and experience deploying large-scale models on multi-GPU clusters, with a strong research and innovation background.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Less than 8 years of experience in robot learning, No experience with PyTorch or large-scale models, Lack of familiarity with robotics toolkits like ROS/ROS2, No research publications or relevant experience
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