Research Staff, LLMs

Deepgram is currently looking for an experienced researcher to who has worked extensively with Large Language Models (LLMS) and has a deep understanding of transformer architecture to join our Research Staff. As a Member of the Research Staff, this individual should have extensive experience working on the hard technical aspects of LLMs, such as data curation, distributed large-scale training, optimization of transformer architecture, and Reinforcement Learning (RL) training.

We are seeking researchers who:

See "unsolved" problems as opportunities to pioneer entirely new approaches

Can identify the one critical experiment that will validate or kill an idea in days, not months

Have the vision to scale successful proofs-of-concept 100x

Are obsessed with using AI to automate and amplify your own impact

If you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative.

Brainstorming and collaborating with other members of the Research Staff to define new LLM research initiatives

Broad surveying of literature, evaluating, classifying, and distilling current methods

Designing and carrying out experimental programs for LLMs

Driving transformer (LLM) training jobs successfully on distributed compute infrastructure and deploying new models into production

Documenting and presenting results and complex technical concepts clearly for a target audience

Staying up to date with the latest advances in deep learning and LLMs, with a particular eye towards their implications and applications within our products

Are passionate about AI and excited about working on state of the art LLM research

Have an interest in producing and applying new science to help us develop and deploy large language models

Enjoy building from the ground up and love to create new systems.

Have strong communication skills and are able to translate complex concepts clearly

Are highly analytical and enjoy delving into detailed analyses when necessary

3+ years of experience in applied deep learning research, with a solid understanding toward the applications and implications of different neural network types, architectures, and loss mechanism

Proven experience working with large language models (LLMs) - including experience with data curation, distributed large-scale training, optimization of transformer architecture, and RL Learning

Strong experience coding in Python and working with Pytorch

Experience with various transformer architectures (auto-regressive, sequence-to-sequence.etc)

Experience with distributed computing and large-scale data processing

Prior experience in conducting experimental programs and using results to optimize models

Deep understanding of transformers, causal LMs, and their underlying architecture

Understanding of distributed training and distributed inference schemes for LLMs

Familiarity with RLHF labeling and training pipelines

Up-to-date knowledge of recent LLM techniques and developments

Published papers in Deep Learning Research, particularly related to LLMs and deep neural networks

Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @ deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.