Machine Learning Engineer

About the role

Skild AI is developing a universal intelligence for robots designed to function in unpredictable environments. You will join a team focused on scaling data-driven machine learning to enable autonomous robotic performance across various real-world tasks.

Key facts

What you'll do

• Create and deploy reinforcement learning algorithms tailored for robotic hardware.
• Build and manage training experiments, including testing models in physical settings.
• Work with the research group to find new ways to scale model training processes.
• Coordinate with deployment and application engineers to move models into production systems.
• Evaluate experimental data to refine model architecture and improve performance.
• Monitor current research trends to incorporate new findings into existing workflows.

Requirements

• BS, MS, or PhD in Engineering, Robotics, Computer Science, or a related discipline, or equivalent professional experience.
• Professional coding ability in C++ or Python.
• Experience with at least one deep learning framework such as JAX, TensorFlow, or PyTorch.
• Practical knowledge of reinforcement learning methods, including model-based, model-free, multi-agent, hierarchical, or multi-task approaches.
• Solid foundation in software engineering, data structures, and algorithms.
• Proven industry background working with robotic systems and reinforcement learning.

Nice to have

• Proficiency with physics simulation software used for training reinforcement learning models.

Skills & tools

• Python
• C++
• PyTorch
• TensorFlow
• JAX
• Reinforcement Learning
• Physics Simulation Engines

Practical notes

Candidates are evaluated based on demonstrated ability and technical aptitude rather than years of experience alone.