Skild AI is building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. They are looking for a Machine Learning Engineer to design and implement cutting-edge reinforcement learning algorithms for robotic applications, impacting the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.
Requirements
- 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.
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.
