- Robot type
- Robot AI and Software
- Location
- San MateoCaliforniaUSA
- Job type
- Hardware
- Posted
- Sep 23, 2024
- Salary
- $100,000–$300,000 a year
Full-time
Robotics Engineer, Manipulation
Job description
We are seeking a versatile Robotics Engineer to develop and implement software solutions for our manipulation systems. The ideal candidate will have experience in controls, perception, and planning. You will be working on deploying state-of-the-art learning-based algorithms on real robot setups, focused on daily manipulation tasks. This role will require close collaboration with researchers and the ML team. The ideal candidate should be comfortable with building high-quality software for robotic manipulation and deploying it on robot hardware.
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing.
Job responsibilities
- Help design algorithms, models, and techniques for various robotic manipulation tasks.
- Design hardware and software systems for various robotic manipulation tasks.
- Write controllers and perception stacks for real-world robotic deployment.
- Write and maintain production-level C++ and Python code for our robotic manipulation platforms.
- Collaborate with machine learning engineers to deploy state-of-the-art models on our robots.
- Continuously improve and optimize robotic software for performance, reliability, and scalability.
Job requirements
- BS, MS or higher degree in Computer Science, Robotics, Engineering or a 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 in Python and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
- Systems-level understanding of the various software modules and their interfaces in a robotic application (ROS/ROS2, simulators, etc.).
- Publications at top-tier ML, robotics or CV conferences (e.g., NeurIPS, ICML, ICLR, CoRL, RSS, ICRA, CVPR, ECCV, ICCV).
- Experience with designing custom robot hardware solutions.
- Proficiency with various robot learning techniques (RL, imitation learning, etc.).