The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in deep learning, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems.
Key job responsibilities
As part of the AGI team, an Applied Scientist will collaborate closely with talented colleagues to lead the development of advanced approaches and modeling techniques, driving forward the frontier of LLM technology.
This includes innovating model-in-the-loop and human-in-the-loop approaches to ensure the collection of high-quality data, safeguarding data privacy and security for LLM training, and more.
An Applied Scientist will also have a direct impact on enhancing customer experiences through state-of-the-art products and services that harness the power of speech and language technology.
A day in the life
An Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience;
while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice.
The ideal candidate should be passionate about delivering experiences that delight customers and creating robust solutions.
They will also create reliable, scalable and high-performance products that require exceptional technical expertise, and a sound understanding of Machine Learning.
We are open to hiring candidates to work out of one of the following locations :
Bellevue, WA, USA
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 1+ years of building models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with Large Language Models (LLMs) or multimodal architectures
PREFERRED QUALIFICATIONS
- PhD degree in Mathematics, Statistics, Engineering, Machine Learning, Computer Science or related discipline
- 4+ years of industry or postdoctoral experience in machine learning
- Experience with patents or publications at top-tier peer-reviewed conferences or journals
- Experience with popular deep learning frameworks including MxNet, PyTorch or TensorFlow
- Experience in building large-scale machine learning systems
- Proficiency in state-of-the-art Natural Language Processing (NLP) and Computer Vision (CV) deep learning models
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