Amazon Backbone Network Planner AMER Development 

United States, Colorado, Denver 

921127063

Key job responsibilities
As part of the AGI-VS team, you will work on solving key industry problems through specialized and optimized models and services. You will lead the development of advanced approaches and modeling techniques, driving forward the frontier of LLM technology. This includes innovation on multi-modal (speech/audio/video) representations, understanding, transformation and generation for streaming and non-streaming applications, learning from human and AI feedback, inference time optimizations, and data efficient scaling.A day in the life
You will support the science solution design, run experiments, research innovative algorithms, and find new ways of optimizing the customer experience, while setting examples for the team on best science practice and standards. You will work closely with talented engineers and scientists to deliver your robust solution to core customers within and outside of Amazon.
Along this you create reliable, scalable and high-performing solutions, demonstrate exceptional technical expertise, and showcase a sound understanding of Machine Learning in general and LLM technology in particular.

- Experience building machine learning models or developing algorithms for business application
- PhD, or a Master's degree and experience in CS, CE, ML or related field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

- PhD
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
- Have publications at top-tier peer-reviewed conferences or journals
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning