Applied AI Research Scientist — LLMs, LMMs & Diffusion

Socket.dev; San Jose (CA); Hybrid; USD 150,000 - 200,000; Full time

Job summary

AMD is seeking an Applied Research Scientist in the San Jose/Seattle hybrid model to advance large language and multimodal models. You will design and train LLMs, LMMs, and diffusion-based image/video generation systems, pushing state-of-the-art through novel architectures and training techniques.

Ideal candidates have PhD/MS in ML/CS/AI and strong Python and ML framework experience (PyTorch, JAX, TensorFlow). You will publish results and engage with academia and open-source communities.

Qualifications

• Experience in developing and debugging in Python.
• Experience in ML frameworks such as PyTorch, JAX or TensorFlow.
• Experience with distributed training.
• Expertise on LLM/LMM/Diffusion pretraining, finetuning, and/or RLHF.
• Familiar with transformer architecture.
• Strong communication and problem-solving skills.
• Publication at top-tier venues is a huge plus.

Responsibilities

• Train and finetune LLMs, LMMs, and image/video generation models.
• Improve on the state-of-the-art LLMs, LMMs, and image/video generation models.
• Accelerate the training and inference speed of LLMs, LMMs, and image/video generation models.
• Research novel ML techniques and model architectures.
• Influence the direction of AMD AI platform.
• Publish your work at top-tier venues.
• Engage with academia and open-source ML communities.

Skills

Python

PyTorch

JAX

TensorFlow

Distributed training

LLM pretraining

Finetuning

RLHF

Transformer

Communication skills

Problem solving

Publications

Education

PhD or Master's in ML/CS/AI

Job description

AMD is seeking an Applied Research Scientist in the San Jose/Seattle hybrid model to advance large language and multimodal models. You will design and train LLMs, LMMs, and diffusion-based image/video generation systems, pushing state-of-the-art through novel architectures and training techniques.

Ideal candidates have PhD/MS in ML/CS/AI and strong Python and ML framework experience (PyTorch, JAX, TensorFlow). You will publish results and engage with academia and open-source communities.