Amazon
Applied Scientist, Generative AI Innovation Center
Amazon, North Reading, Massachusetts, United States, 01814
Overview
Applied Scientist, Generative AI Innovation Center – AWS/Korea. This role focuses on applying Generative AI algorithms to solve real-world problems with significant impact within the Generative AI Innovation Center, a team of strategists, scientists, engineers, and architects working with customers to build bespoke solutions that harness generative AI. Beginning in 2024, the Custom Model and Optimization program helps customers develop and scale highly customized generative AI solutions, including imagining and scoping use cases, navigating technical or business challenges, developing and optimizing models, and planning for launch at scale. The GenAI Innovation Center provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers, design and run experiments, research new algorithms, and explore ways to optimize risk, profitability, and customer experience. The team seeks Applied Scientists capable of designing, evangelizing, and implementing state-of-the-art GenAI solutions for novel problems. Key responsibilities
Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges Interact with customers directly to understand their business problems, aid in implementation of generative AI solutions, brief customers, and guide adoption patterns and paths to production Help customers optimize their solutions through model selection, training or tuning, right-sizing, distillation, and hardware optimization Provide customer and market feedback to product and engineering teams to help define product direction A day in the life
This is a customer-facing role. You may be required to travel to client locations and deliver professional services as needed. About the team
Sales, Marketing and Global Services (SMGS) within AWS Sales, Marketing, and Global Services. The role sits in the Professional Services context within Global Services. Qualifications
BASIC QUALIFICATIONS
PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field, or Master’s degree plus 5 years of relevant work experience 5+ years of hands-on experience with Python to build, train, and evaluate models 2+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies Scientific publication track record at top-tier AI/ML/NLP conferences or journals PREFERRED QUALIFICATIONS
Experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques Experience building LLM-powered agentic workflows, orchestration, and agent customization Experience with model optimization techniques (quantization, distillation, compression, inference optimization, etc.) Hands-on experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Strong communication skills with the ability to convey rigorous technical concepts to non-experts Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Equal Opportunity
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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Applied Scientist, Generative AI Innovation Center – AWS/Korea. This role focuses on applying Generative AI algorithms to solve real-world problems with significant impact within the Generative AI Innovation Center, a team of strategists, scientists, engineers, and architects working with customers to build bespoke solutions that harness generative AI. Beginning in 2024, the Custom Model and Optimization program helps customers develop and scale highly customized generative AI solutions, including imagining and scoping use cases, navigating technical or business challenges, developing and optimizing models, and planning for launch at scale. The GenAI Innovation Center provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers, design and run experiments, research new algorithms, and explore ways to optimize risk, profitability, and customer experience. The team seeks Applied Scientists capable of designing, evangelizing, and implementing state-of-the-art GenAI solutions for novel problems. Key responsibilities
Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges Interact with customers directly to understand their business problems, aid in implementation of generative AI solutions, brief customers, and guide adoption patterns and paths to production Help customers optimize their solutions through model selection, training or tuning, right-sizing, distillation, and hardware optimization Provide customer and market feedback to product and engineering teams to help define product direction A day in the life
This is a customer-facing role. You may be required to travel to client locations and deliver professional services as needed. About the team
Sales, Marketing and Global Services (SMGS) within AWS Sales, Marketing, and Global Services. The role sits in the Professional Services context within Global Services. Qualifications
BASIC QUALIFICATIONS
PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field, or Master’s degree plus 5 years of relevant work experience 5+ years of hands-on experience with Python to build, train, and evaluate models 2+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies Scientific publication track record at top-tier AI/ML/NLP conferences or journals PREFERRED QUALIFICATIONS
Experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques Experience building LLM-powered agentic workflows, orchestration, and agent customization Experience with model optimization techniques (quantization, distillation, compression, inference optimization, etc.) Hands-on experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker Strong communication skills with the ability to convey rigorous technical concepts to non-experts Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Equal Opportunity
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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