Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are seeking a versatile Robotics Manipulation & Controls 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.
Responsibilities
- Help design algorithms, models, and techniques for various robotic manipulation tasks.
- Design hardware and software systems for various robotic manipulation tasks.
- Write controllers, planners, 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.
Preferred Qualifications
- 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.).
- Experience working with modern computer vision algorithms, sensors (LiDAR, camera, radar, etc.), 3D (meshes, point clouds, etc.), segmentation, tracking, object detection.
