Robotics Manipulation Engineer — ML-Driven Real-World

Skild; San Mateo (CA); On-site; USD 100,000 - 300,000; Full time

Job summary

Skild AI in California seeks a versatile Robotics Engineer to develop and deploy software for manipulation systems on real robots. You will work on controllers, perception stacks, and planning, collaborating closely with researchers and the ML team to bring learning-based algorithms to life on hardware.

The role emphasizes high-quality C++/Python software, ROS/ROS2 integration, and a strong foundation in robotics concepts such as kinematics, dynamics, and SLAM. On-site work in San Mateo, CA.

Qualifications

• BS, MS or higher in Computer Science, Robotics, Engineering or related field, or equivalent practical experience.
• Experience in designing robotic manipulation systems and deploying software on real robots.
• Experience with writing controllers and knowledge of robotics (e.g., kinematics, dynamics, control, motion planning, SLAM).
• Proficiency with Python and at least one deep learning library (PyTorch, TensorFlow, JAX).
• Knowledge of ROS/ROS2 and simulators for robotic applications.
• Publications at top-tier ML/robotics conferences are a plus.
• Experience designing custom robot hardware solutions.
• Experience with RL or imitation learning and computer vision techniques.

Responsibilities

• Help design algorithms, models, and techniques for various robotic manipulation tasks.
• Write controllers and perception stacks for real-world robotic deployment.
• Collaborate with ML engineers to deploy state-of-the-art models on our robots.
• Continuously improve and optimize robotic software for performance, reliability, and scalability.

Skills

C++

Python

ROS/ROS2

Machine learning basics

Computer vision

Education

BS, MS or higher in CS/Robotics/Engineering or related field

Tools

PyTorch

TensorFlow

JAX

Job description

Skild AI in California seeks a versatile Robotics Engineer to develop and deploy software for manipulation systems on real robots. You will work on controllers, perception stacks, and planning, collaborating closely with researchers and the ML team to bring learning-based algorithms to life on hardware.

The role emphasizes high-quality C++/Python software, ROS/ROS2 integration, and a strong foundation in robotics concepts such as kinematics, dynamics, and SLAM. On-site work in San Mateo, CA.