AI Research Intern: RL & LLM Post-Training

Advanced Micro Devices, Inc.; Santa Clara (CA); Híbrido; USD 34.000 - 55.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Paid internship

Hybrid/Onsite options

Descripción de la vacante

AMD is seeking an AI Research Intern in Santa Clara, CA for Summer 2027. You will work on RL and LLM post-training, researching and prototyping methods with supervision from a world-class team.

The role is full-time as a co-op/internship, with hybrid or onsite arrangements, running May to August 2027 (or June–Sept for quarter schedules). Ideal candidates are pursuing a PhD in CS/ML with strong PyTorch experience.

Formación

• Currently pursuing a PhD in CS, ML, EE, or a related field.
• Strong knowledge of reinforcement learning and modern deep-learning methods.
• Experience implementing ML models in Python with PyTorch.
• Familiarity with LLM post-training, RLHF/RLAIF, or language/code agents.
• Track record of reproducible experiments and empirical analysis.
• Publications at top ML/CV conferences preferred.
• Experience with GPU computing or distributed training is beneficial.

Responsabilidades

• Research and prototype RL methods for post-training language and code models.
• Explore policy optimization, preference learning, reward modeling, exploration, and credit assignment.
• Design and run controlled experiments with verifiable feedback.
• Analyze failure modes such as reward hacking, policy degeneration, and training instability.
• Develop evaluation methods reflecting realistic engineering constraints.
• Collaborate with research and infrastructure on rollout generation, training, logging, and reproducibility.
• Document findings and contribute to technical reports and publications.

Conocimientos

Reinforcement Learning

Python

PyTorch

Experiment design

Research methods

Educación

PhD in Computer Science / ML / EE

Herramientas

PyTorch

Descripción del empleo

AMD is seeking an AI Research Intern in Santa Clara, CA for Summer 2027. You will work on RL and LLM post-training, researching and prototyping methods with supervision from a world-class team.

The role is full-time as a co-op/internship, with hybrid or onsite arrangements, running May to August 2027 (or June–Sept for quarter schedules). Ideal candidates are pursuing a PhD in CS/ML with strong PyTorch experience.