LLM Researcher: Transformer R&D & Scalable Training

Deepgram; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Deepgram is seeking an experienced Research Staff member to advance large language models and transformer architectures. You will design and run distributed training experiments, curate data, and push production-ready models.

You will collaborate with the research team to publish results, stay current with DL/LLM advances, and translate complex concepts for broad audiences within our AI-first culture.

Qualifications

• 3+ years of experience in applied deep learning research.
• Proven experience working with large language models (LLMs) including data curation, distributed training, transformer optimization, and RL.
• Strong experience coding in Python and working with PyTorch.
• Experience with distributed computing and large-scale data processing.
• Prior experience in conducting experimental programs and using results to optimize models.

Responsibilities

• Brainstorming and collaborating with 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 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 and their applications within our products.

Skills

LLMs research

Distributed training

Transformer architectures

Model optimization

Experimental design

AI research vision

Tools

Python

PyTorch

Job description

Deepgram is seeking an experienced Research Staff member to advance large language models and transformer architectures. You will design and run distributed training experiments, curate data, and push production-ready models.

You will collaborate with the research team to publish results, stay current with DL/LLM advances, and translate complex concepts for broad audiences within our AI-first culture.