PhD AI Research Infra Intern — RL Post-Training

Advanced Micro Devices

Santa Clara (CA)

Hybrid

USD 50,000 - 67,000

Full time

4 days ago
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Job summary

Advanced Micro Devices in Santa Clara, CA is seeking a passionate AI Research intern who is currently pursuing a PhD in CS/ML/AI. You will work full time in a hybrid or onsite setup this Summer 2027, developing RL-based post-training infra for large models and building scalable tools for experimentation and deployment.

You should have strong Python and PyTorch skills, plus experience with RL, distributed training, and multi-GPU workloads.

Qualifications

  • Pursuing a PhD in CS/ML/AI or related field.
  • Strong Python and PyTorch programming skills.
  • Experience with RL, RLHF/RLAIF or preference optimization.
  • Experience with distributed training and large-scale inference.

Responsibilities

  • Develop and optimize RL-based post-training infrastructure for LLMs and multimodal models.
  • Build scalable rollout generation, inference, reward computation and policy updates.
  • Improve distributed training efficiency, reliability and memory usage.
  • Design interfaces for researchers to implement RL algorithms quickly.
  • Create tools for experiment config, logging, checkpointing and monitoring.
  • Profile end-to-end training pipelines and resolve bottlenecks.
  • Support on-policy and off-policy training workflows with verifiable feedback.
  • Document system designs and contribute to technical reports.

Skills

Python
PyTorch
Reinforcement learning
RLHF/RLAIF
Distributed training

Education

PhD in Computer Science or related field

Tools

Experiment tracking
Containerization
Cluster environments

Job description

Advanced Micro Devices in Santa Clara, CA is seeking a passionate AI Research intern who is currently pursuing a PhD in CS/ML/AI. You will work full time in a hybrid or onsite setup this Summer 2027, developing RL-based post-training infra for large models and building scalable tools for experimentation and deployment.

You should have strong Python and PyTorch skills, plus experience with RL, distributed training, and multi-GPU workloads.

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