6 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
Skild AI builds a general-purpose robotic intelligence and software stack to train and deploy robots that adapt to varied, unseen tasks for commercial use. It offers a platform and models for robot manufacturers and enterprises automating physical work, with support for integration across manipulators and mobile systems. Founded in 2023 and headquartered in Pittsburgh, the privately held company raised a Series C in 2026.