Amazon
Senior Applied Scientist, Artificial General Intelligence
Amazon, Boston, Massachusetts, us, 02298
Job ID: 2853182 | Amazon.com Services LLC
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to build industry-leading technology with Large Language Models (LLMs) and multi-modal systems. You will lead projects that work on cutting edge technologies including multi-modal model alignment, moderation systems and evaluation.
Key job responsibilities As a Senior Applied Scientist with the AGI team, you will lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI). You are also expected to publish in top tier conferences.
About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems. Specifically, we focus on model alignment with an aim to maintain safety while not denting utility, in order to provide the best-possible experience for our customers. BASIC QUALIFICATIONS
- PhD, or Master's degree and 5+ years of applied research experience - 5+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning PREFERRED QUALIFICATIONS
- PhD in Computer Science, Electrical Engineering, Mathematics or related field - Strong experience with multi-modal model alignment, moderation systems, and evaluation with Generative Artificial Intelligence (GenAI) - Experience with patents or publications at top-tier peer-reviewed conferences or journals - Experience with popular deep learning frameworks, including PyTorch Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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Key job responsibilities As a Senior Applied Scientist with the AGI team, you will lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI). You are also expected to publish in top tier conferences.
About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems. Specifically, we focus on model alignment with an aim to maintain safety while not denting utility, in order to provide the best-possible experience for our customers. BASIC QUALIFICATIONS
- PhD, or Master's degree and 5+ years of applied research experience - 5+ years of building machine learning models for business application experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning PREFERRED QUALIFICATIONS
- PhD in Computer Science, Electrical Engineering, Mathematics or related field - Strong experience with multi-modal model alignment, moderation systems, and evaluation with Generative Artificial Intelligence (GenAI) - Experience with patents or publications at top-tier peer-reviewed conferences or journals - Experience with popular deep learning frameworks, including PyTorch Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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