Principal Applied Research Scientist

Principal Applied Research Scientist

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you'll discover the real differentiator is our culture.

We push the limits of innovation to solve the world's most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.

We are looking for a Principal Applied Research Scientist who is experienced with training large language models and/or large multimodal models. In this role, you will explore novel LLM/LMM architectures and large-scale training techniques to advance the state-of-the-arts. You will be part of a world-class research team working on pre-training, fine-tuning, RL, and aligning large language and multimodal models, in addition to keeping up-to-date to the latest progress and trends in LLM/LMM and foundation models.

The ideal candidate should be passionate about software engineering and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD.

Key Responsibilities:

• Train, finetune, and RL for LLMs/LMMs.
• Improve on the state-of-the-art LLMs/LMMs..
• Accelerate the training and inference speed of LLMs/LMMs.
• Research novel ML techniques and model architectures.
• Influence the direction of AMD AI platform.
• Publish your work at top-tier venues.

Preferred Experience:

• Experience in developing and debugging in Python.
• Experience in ML Framework such as PyTorch, JAX or Tensor Flow
• Experience with distributed training.
• Expertise on LLM/LMM pretraining, fine tuning, and/or RL.
• Expertise on transformer architecture.
• Strong publication record in top tier conferences and journals.

Academic Credentials:

• A PhD degree or equivalent in machine learning, computer science, artificial intelligence, or a related field.

Location:

Bellevue, WA or San Jose, CA preferred (hybrid). May consider other US locations.