Tactile AI Research Engineer - Special Projects (Robotics)
Apple
1 day ago
Contract
On-site
Santa Clara, California, United States
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: \\n\\nPassion for the mission: We’re here to make something extraordinary. We seek whatever work is right and strive for the best possible results. \\nModesty: The right answer is more significant than being right. We search for solutions as a team and value clear-eyed feedback. \\nLean habits: You can’t grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make phenomenal decisions.
Implement and train state-of-the-art machine learning models for tactile-enabled robotic systems.\\nOptimize and deploy machine learning models on physical systems, ensuring policing durability across sim-to-real-gaps.\\nCurate and generate training data from simulation and real-world demonstrations ensuring adequate coverage of complex contact physics.\\nEstablish evaluation metrics and testing protocols to benchmark policy performance.\\nCollaborate across disciplines leverage expertise and advance impact across multiple stakeholders.\\nDocument research findings, methodologies, and technical developments for internal knowledge sharing and external publications.
3+ years of relevant experience successfully deploying tactile-based policies in robotics.\\nStrong proficiency in Python and C++ with experience in complex, multi-language systems.\\nExpertise in machine learning algorithms and deep learning frameworks such as PyTorch and TensorFlow.\\nStrong software engineering skills, delivering clean, well-tested, and optimized code.\\nStrong analytical, troubleshooting, and problem-solving skills.\\nAbility to work effectively in multidisciplinary teams.\\nBachelor’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.\\nStrong foundation in robot kinematics, dynamics, motion planning, and control.\\nExperience with a wide range of physics simulation software and their contact mechanics (e.g. Mujoco, IssacLab simulator, Drake, etc.).\\nSuccessful record of employing machine learning techniques to achieve useful system performance.
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: \\n\\nPassion for the mission: We’re here to make something extraordinary. We seek whatever work is right and strive for the best possible results. \\nModesty: The right answer is more significant than being right. We search for solutions as a team and value clear-eyed feedback. \\nLean habits: You can’t grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make phenomenal decisions.
Implement and train state-of-the-art machine learning models for tactile-enabled robotic systems.\\nOptimize and deploy machine learning models on physical systems, ensuring policing durability across sim-to-real-gaps.\\nCurate and generate training data from simulation and real-world demonstrations ensuring adequate coverage of complex contact physics.\\nEstablish evaluation metrics and testing protocols to benchmark policy performance.\\nCollaborate across disciplines leverage expertise and advance impact across multiple stakeholders.\\nDocument research findings, methodologies, and technical developments for internal knowledge sharing and external publications.
3+ years of relevant experience successfully deploying tactile-based policies in robotics.\\nStrong proficiency in Python and C++ with experience in complex, multi-language systems.\\nExpertise in machine learning algorithms and deep learning frameworks such as PyTorch and TensorFlow.\\nStrong software engineering skills, delivering clean, well-tested, and optimized code.\\nStrong analytical, troubleshooting, and problem-solving skills.\\nAbility to work effectively in multidisciplinary teams.\\nBachelor’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.\\nStrong foundation in robot kinematics, dynamics, motion planning, and control.\\nExperience with a wide range of physics simulation software and their contact mechanics (e.g. Mujoco, IssacLab simulator, Drake, etc.).\\nSuccessful record of employing machine learning techniques to achieve useful system performance.