The company is looking to develop intelligent, adaptable robots capable of learning and performing complex tasks autonomously.
Requirements
- Proficiency in Python, C++, or similar
- At least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
- Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.)
- Strong background in algorithms, data structures, and software engineering principles
- Experience with physics simulation engines and tools for training RL
- Deep understanding of state-of-the-art machine learning techniques and models
Responsibilities
- Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications
- Design and conduct experiments to train RL models and conduct real-world tests
- Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training
- Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment
- Analyze and interpret experimental results, iterating on model design to achieve desired performance
- Stay up-to-date with the latest research and advancements in reinforcement learning
Other
- BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience
- Extensive industry experience with reinforcement learning and robotic systems
