PhD Gen AI & RL Research Intern — AI Systems & Evaluation

Advanced Micro Devices, Inc.; Santa Clara (CA); Hybrid; USD 34,000 - 55,000; Full time

Job summary

Advanced Micro Devices, Inc. (AMD) invites a PhD student to intern in AI research at the Santa Clara campus. You will work full-time during the summer in a hybrid or onsite setup, contributing to cutting-edge post-training model research and evaluations.

The role emphasizes reinforcement learning, deep learning with PyTorch, and reproducible experiments, with opportunities to publish findings and collaborate with cross-functional teams.

Qualifications

• Currently pursuing a PhD in Computer Science, ML, AI, ECE, or related field.
• Strong knowledge of reinforcement learning and modern deep-learning methods.
• Experience implementing and evaluating ML models using Python and PyTorch.
• Familiarity with LLM post-training, RLHF/RLAIF, or language and multimodal agents.

Responsibilities

• Research and prototype methods for post-training large generative models.
• Explore policy optimization, preference learning, reward modeling, exploration, and credit assignment techniques.
• Develop methods for improving reasoning, code generation, tool use, and agentic behavior.
• Design and run controlled experiments with verifiable, preference-based, or model-generated feedback.
• Analyze failure modes such as reward hacking, policy degeneration, and training instability.
• Develop evaluations measuring model quality, robustness, safety, and real-world task performance.
• Collaborate with research and infrastructure teams on training, rollout generation, logging, and reproducibility.
• Document findings and contribute to technical reports and publications.

Skills

Reinforcement learning

Python

PyTorch

Deep learning

Experiment reproducibility

Research publications

Education

PhD in Computer Science / ML / AI / ECE

Tools

PyTorch

GPU computing

Distributed systems

Job description

Advanced Micro Devices, Inc. (AMD) invites a PhD student to intern in AI research at the Santa Clara campus. You will work full-time during the summer in a hybrid or onsite setup, contributing to cutting-edge post-training model research and evaluations.

The role emphasizes reinforcement learning, deep learning with PyTorch, and reproducible experiments, with opportunities to publish findings and collaborate with cross-functional teams.