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Skild AI is building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing, aiming for widespread deployment of robots within society through data-driven machine learning.

Requirements

• Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
• Understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
• Experience with physics simulation engines and tools for training RL.
• 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.

Other

• Currently pursuing a BS, MS, or higher degree in Computer Science, Robotics, Engineering, or a related field, or equivalent practical experience.
• Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude.
• Passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.