THE ROLE: We are looking for an Applied Research Scientist experienced with training large language models, large multimodal models, and image/video generation models. In this role, you will explore novel LLM/LMM and image/video generation 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, and aligning large language models, large multimodal models, and image/video generation models, in addition to keeping up-to-date to the latest progress and trends in LLM/LMM, image/video generation, and other foundation models.
THE PERSON:Do you like to design and implement novel research ideas, improve the quality of the large language/multimodal models, accelerate the training and inference speed of LLMs, LMMs, and image/video generation models, and influence future hardware and software direction? If so, this role is for you. The ideal candidate will have expertise and hands-on experience on training LLMs, LMMs, and/or diffusion models., familiar with hyper-parameter tuning techniques, data preprocessing, tokenization methods and latest training approaches for LLMs, LMMs, and diffusion models. A successful candidate needs to be knowledgeable with latest transformer architectures.
KEY 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.
PREFERRED EXPERIENCE:- 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.
ACADEMIC CREDENTIALS:- A PhD or master's degree or equivalent in machine learning, computer science, artificial intelligence, or a related field.
LOCATION:San Jose, CA or Seattle, WA areas preferred (Hybrid).
This role is not eligible for visa sponsorship.#LI-MV1
#HYBRID
Benefits offered are described: AMD benefits at a glance.
