Research Engineer, Agents
AnthropicFull Time
Junior (1 to 2 years)
Candidates should possess 3+ years of experience working extensively with Large Language Models (LLMs) and have a deep understanding of transformer architecture. Experience with data curation, distributed large-scale training, optimization of transformer architecture, and Reinforcement Learning (RL) training is required. Strong communication skills and the ability to translate complex concepts clearly are also essential.
The Research Staff member will brainstorm and collaborate on new LLM research initiatives, survey and evaluate current literature, and design and execute experimental programs for LLMs. Responsibilities include driving transformer (LLM) training jobs on distributed infrastructure, deploying new models into production, documenting and presenting results, and staying current with advances in deep learning and LLMs.
Speech recognition APIs for audio transcription
Deepgram specializes in artificial intelligence for speech recognition, offering a set of APIs that developers can use to transcribe and understand audio content. Their technology allows clients, ranging from startups to large organizations like NASA, to process millions of audio minutes daily. Deepgram's APIs are designed to be fast, accurate, scalable, and cost-effective, making them suitable for businesses needing to handle large volumes of audio data. The company operates on a pay-per-use model, where clients are charged based on the amount of audio they transcribe, allowing Deepgram to grow its revenue alongside client usage. With a focus on the high-growth market of speech recognition, Deepgram is positioned for future success.