Summer 2027 Master's AI Research, Reinforcement Learning and LLM Post-Training Intern
Santa Clara, CA$83.2k - $124.8kUNAVAILABLEPosted 4w ago
About the role
Internship at AMD focused on AI research in reinforcement learning and large language models, with hands-on prototyping, experimentation, and collaboration across research and infrastructure teams. Open to master's students in relevant fields, onsite in Santa Clara, CA for Summer 2027.
Responsibilities
- Research and prototype RL methods for post-training language and code models.
- Explore policy optimization, preference learning, reward modeling, exploration, and credit-assignment techniques.
- Design and run controlled experiments using verifiable, preference-based, or simulator-generated feedback.
- Analyze failure modes such as reward hacking, policy degeneration, and training instability.
- Develop evaluation methods that reflect realistic engineering constraints.
- Collaborate with research and infrastructure teams on rollout generation, training, logging, and reproducibility.
- Document findings and contribute to technical reports and publications.
Qualifications
- Must be currently pursuing a MS in Computer Science, Machine Learning, Electrical or Computer Engineering, or a related field.
- Knowledge of reinforcement learning and modern deep-learning methods.
- Experience implementing and evaluating machine-learning models using Python and frameworks such as PyTorch.
- Familiarity with LLM post-training, RLHF/RLAIF, preference optimization, or language and code agents.
- Experience conducting reproducible experiments and analyzing empirical results.
- Publications at leading machine-learning or computer-vision conferences (preferred).
- Exposure to GPU computing or distributed training (beneficial).
- Familiarity with compilers, kernels, optimization, EDA workflows, or large-scale codebases (plus).
Skills
Required:Reinforcement LearningPythonPyTorch
Nice to have:LLM post-training / RLHF / RLAIF
Benefits
- AMD benefits at a glance
Last updated Oct 15, 2026. Interested? Apply on the company site.
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