2026 Intern, On Device Physical AI (Summer)

Position Summary:

You are passionate about building high performance on-device physical AI systems. In this role, you will be researching end-to-end machine learning computation, on-device, real-time vision pipelines with physical AI. The candidate will work with the Samsung robotics team to integrate, design, and innovate efficient on-device physical AI model system and training pipeline for robotics and physical AI (e.g. VLM, VLA), deliver low power, low latency control, and support spatial perception and reasonings for autonomous systems.

Position Responsibilities:

• Conduct research on end-to-end machine learning computation and real-time vision pipelines specifically for physical AI and robotics.
• Design, innovate, and test efficient, on-device physical AI model systems and training pipelines (focusing on VLM and VLA architectures).
• Implement system architectures that deliver low-power, low-latency control for autonomous systems.
• Develop and support adaptive in-scene logic to enhance the capabilities of autonomous robotics.
• Perform on-device and embedded system programming, utilizing skills in kernel optimization and instruction set programming.
• Work closely with the Samsung robotics team to integrate these new AI models into physical systems (potentially utilizing ROS, but prior ROS experiences not required).

Required Skills:                                                 

• Currently pursuing a Ph.D. in a relevant technology field at a top ranked university (e.g. Computer Science, Electrical Engineering, other etc.), or Masters with prior relevant industrial experiences
• Machine learning computation system or parallel computing for VLM and/or VLA
• Prior exposure to robotics simulation experience (Issac Sim, mujoco, etc.)
• System architecture (memory, computation) and ML model architecture
• On device and/or embedded system programming
• Real-time computer vision system, ideally, with 3D real-time vision experiences
• In-context learning and/or spatial reasoning research
• Good communication skills and good team player

Preferred Qualifications:

• Solid understanding of real time vision pipelines, latency tight architectures for autonomous control is a plus
• Prior in-context learning and/or spatial reasoning research is a plus
• Strong system programming skills, including kernel optimizations, instruction set programming, real-time/embedded programming skills, plus
• Worked on physical AI or robotics systems and are familiar with ROS is a plus
• Prior publications on the topic is a plus (ICML, ICLR, CVPR, ICCV, ICRA, RSS)

Special Attributes:

• Positive attitude and energy, imagination, resilience, flexibility and resourcefulness
• Clear communication skills, strong team player
• Resilience to overcome hurdles and address failures with alternative paths