4 months ago
Base Salary
$100k - $300k/yr
Responsibilities
- Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
- Design and conduct experiments to train reinforcement learning models and perform real-world tests.
- Collaborate with researchers on methods for scaling reinforcement learning model training.
- Work with inference, application, and deployment engineers to integrate reinforcement learning models into robotic systems and improve robust deployment.
- Analyze experimental results and iterate on model designs to achieve target performance.
- Stay current with research and advances in reinforcement learning.
Requirements
- Bachelor’s, master’s, or higher degree in Computer Science, Robotics, Engineering, or a related field, or equivalent practical experience.
- Proficiency in Python, C++, or a similar language and at least one deep learning library such as PyTorch, TensorFlow, or JAX.
- Practical experience with reinforcement learning algorithms and techniques, including model-free, model-based, multi-task, hierarchical, and multi-agent methods.
- Strong background in algorithms, data structures, and software engineering principles.
- Experience with physics simulation engines and tools for reinforcement learning training.
- Deep understanding of current machine learning techniques and models.
- Extensive industry experience with reinforcement learning and robotic systems.
Categories
ML EngineeringRobotics
About Skild AI
Building general purpose robotic intelligence.