Senior Applied Scientist , Generative AI, AGI Inference Engine

The Artificial General Intelligence (AGI) Inference Engine team is looking for a highly-skilled Senior Applied Scientist, to lead the research and implementation of novel techniques to push the boundaries of efficient inference for Generative Artificial Intelligence (GenAI) models.


Key job responsibilities
Explore emerging inference optimization techniques for LLMs and diffusion models
Design and conduct experiments, analyze results and influence Amazon AGI roadmap by providing recommendations
Collaborate with cross-functional teams of engineers and scientists to identify and solve complex problems in GenAI
Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems
Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports

A day in the life
Senior Applied Scientists in our team are independent and have much freedom in the way they contribute. They read recent papers, explore ideas, brainstorm and freely connect with others to cooperate. They detect, investigate and resolve complex problems, sometimes through creating software solutions, and sometimes just through finding and reusing something that exists. They partner with leaders to focus on right things and make good decisions.

About the team
Our mission is to build best-in-class, fast, accurate, and cost-efficient large language and diffusion model inference solutions and infrastructure that will enable Amazon businesses to deliver more value to their customers.

Basic Qualifications

3+ years of research experience
PhD, or Master's degree and 6+ years of applied research experience
Experience with neural deep learning methods and machine learning
Knowledge of Machine Learning algorithms and techniques

Preferred Qualifications

PhD in Computer Science, Machine Learning, or a related field, with a focus on GenAI
Experience in developing and implementing algorithms for LLMs and/or diffusion models inference
Programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch
Excellent problem-solving skills, with the ability to think creatively and critically about complex problems
Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
Experience with patents or publications at top-tier peer-reviewed conferences or journals

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