Tactile AI Research Engineer - Special Projects (Robotics

We are seeking research scientists and engineers with strong backgrounds across mechatronics, controls, haptics, robotics, simulation, and machine learning to drive breakthrough innovations in intelligent robotic systems. This position requires a hands-on approach, integrating software and hardware solutions to push the boundaries of perception, control, and intelligence. You will work alongside world-class researchers and engineers, contributing to technologies that power the Apple ecosystem.

We are a team of best-in-the-world research scientists and engineers with deep experience in computer vision, machine learning, robotics, haptics, and related areas. We work on exciting new technologies that bring joy to millions of people. In our daily work, the team stays innovative, productive, and fun by sharing some key values:
Passion for the mission:
We're here to make something extraordinary. We seek whatever work is right and strive for the best possible results. Modesty:
The right answer is more significant than being right. We search for solutions as a team and value clear-eyed feedback. Lean habits:
You can't grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make phenomenal decisions.

• 3+ years of relevant experience successfully deploying tactile-based policies in robotics.
• Strong proficiency in Python and C++ with experience in complex, multi-language systems.
• Expertise in machine learning algorithms and deep learning frameworks such as PyTorch and Tensor Flow.
• Strong software engineering skills, delivering clean, well-tested, and optimized code.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to work effectively in multidisciplinary teams.
• Bachelor’s, Master’s, or PhD degree in Engineering, Robotics, Computer Science, or a related field.

• Functional understanding of tactile sensing and haptics technologies to solve challenges in interaction and manipulation.
• Strong foundation in robot kinematics, dynamics, motion planning, and control.
• Experience with a wide range of physics simulation software and their contact mechanics (e.g. Mujoco, Issac Lab simulator, Drake, etc.).
• Successful record of employing machine learning techniques to achieve useful system performance.