Technical Program Manager Intern, AI Research (PhD) - Hybrid

Advanced Micro Devices; Santa Clara (CA); On-site; USD 34,000 - 48,000; Full time

Job summary

Advanced Micro Devices (AMD) is seeking an AI Research Program Manager intern/co-op in Santa Clara, CA for Summer 2027. You will join a team working at the AI ecosystem's core, coordinating research roadmaps, datasets, and experiment schedules while collaborating with researchers and engineers to push ML progress.

PhD candidates in technical fields with ML/RLHF familiarity are encouraged to apply; candidates should thrive in ambiguous settings, communicate clearly, and contribute to cross-team

Qualifications

• Foundational understanding of machine learning, reinforcement learning, generative AI, or ML systems.
• Experience coordinating technical projects through coursework, research, internships, or extracurricular activities.
• Familiarity with AI research, ML, or software engineering projects is a plus.

Responsibilities

• Support research roadmaps, milestones, experiment schedules, and dependency tracking.
• Coordinate datasets, evaluation systems, compute requirements, and deliverables across teams.
• Organize experiment reviews, decision records, and follow-up actions.
• Track benchmark performance, reproducibility, stability, risks, and blockers.
• Support GPU capacity planning and experiment prioritization.
• Prepare concise program updates for technical and leadership audiences.
• Document requirements and evaluation criteria for research-to-engineering handoffs.

Skills

ML foundations

Project coordination

AI/ML systems familiarity

LLM/RLHF terminology

Education

PhD in technical field

Job description

Advanced Micro Devices (AMD) is seeking an AI Research Program Manager intern/co-op in Santa Clara, CA for Summer 2027. You will join a team working at the AI ecosystem's core, coordinating research roadmaps, datasets, and experiment schedules while collaborating with researchers and engineers to push ML progress.

PhD candidates in technical fields with ML/RLHF familiarity are encouraged to apply; candidates should thrive in ambiguous settings, communicate clearly, and contribute to cross-team