Machine Learning Engineer

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.

Preferred Qualifications:

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Proficiency in Python, C++, or similar and 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.
• Extensive industry experience with reinforcement learning and robotic systems.