Research Intern, Physical AI and GPU (PhD)
Marvell Technology, Inc.Match Score
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Job Description
Structured overview of role & requirementsAbout This Role
Prototype and validate next-generation Physical AI platforms focusing on AI systems with constrained compute and low-end GPUs.
Write and optimize CUDA code for kernel performance, memory management, and tuning under resource constraints.
Design, train, and deploy ML models for perception, reasoning, and real-time autonomous agentic systems on physical platforms.
Minimum Requirements
Currently enrolled in PhD, MS by Research, or MTech by Research in CS, CE, Electronics, EE, Robotics, or related field.
Strong GPU and CUDA programming skills including kernel optimization and memory management.
Proficiency in C/C++ and Python programming.
Experience with machine learning fundamentals, systems, and robotic or real-world AI applications.
Ideal Candidate Profile
Comfortable working on hardware-constrained AI systems targeting real-world autonomous agents and Physical AI platforms.
Skilled in integrating ML modeling and training (PyTorch or TensorFlow) with systems and architecture knowledge.
Experience or interest in robotics frameworks, model optimization for constrained devices, and agentic/autonomous system development.