Amazon
Applied Science Manager, Generative AI Innovation Center, AWS
Amazon, Seattle, Washington, us, 98127
Applied Science Manager, Generative AI Innovation Center, AWS
Job ID: 3089408 | Amazon Web Services Japan GK
Amazon launched the Generative AI Innovation Center (GAIIC) in June 2023 to help AWS customers accelerate the use of Generative AI to solve business and operational problems and promote innovation in their organization (https://press.aboutamazon.com/2023/6/aws-announces-generative-ai-innovation-center).
GAIIC provides opportunities to innovate in a fast‑paced organization that contributes to game‑changing projects and technologies that get deployed on devices and in the cloud.
Key job responsibilities: As an Applied Science Manager in GAIIC, you’ll partner with technology and business teams to build new GenAI solutions that delight our customers. You will be responsible for directing a team of data/research/applied scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, and deliver state‑of‑the‑art solutions to customers’ business and mission problems. Your team will be working with terabytes of text, images and other types of data to address real‑world problems.
The successful candidate will possess both technical and customer‑facing skills that will allow you to be the technical “face” of AWS within our solution‑providers’ ecosystem/environment as well as directly to end customers. You will drive discussions with senior technical and management personnel within customers and partners, and provide the technical background that enables them to interact with and give guidance to data/research/applied scientists and software developers.
The ideal candidate will also have a demonstrated ability to think strategically about business, product and technical issues. Finally, of critical importance, the candidate will be an excellent technical team manager, someone who knows how to hire, develop and retain high‑quality technical talent.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption and growth from the largest and fastest‑growing small‑ and mid‑market accounts to enterprise‑level customers including the public sector. The AWS Global Support team interacts with leading companies and believes that world‑class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission‑critical applications on top of AWS services.
About the team: AWS Global Services includes experts from across AWS who help our customers design, build, operate and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in this job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?: Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture: AWS values curiosity and connection. Our employee‑led and company‑sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by bold ideas, fresh perspectives and passionate voices our teams bring to everything we do.
Mentorship & Career Growth: We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge‑sharing, mentorship and other career‑advancing resources here to help you develop into a better‑rounded professional.
Work/Life Balance: We value work‑life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
Basic Qualifications
Japanese fluency, Business English
PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field plus 5 years of relevant experience; or Master’s degree plus 10 years of relevant work experience
5+ years of hands‑on experience with Python to build, train and evaluate models
5+ 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
2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post‑training, continual pre‑training, fine‑tuning or reinforcement learning techniques
Scientific publication track record at top‑tier AI/ML/NLP conferences or journals
Experience directly managing scientists or machine learning engineers
Preferred Qualifications
Demonstrated experience with building LLM‑powered agentic workflow, orchestration and agent customization
Experience with model optimization techniques (quantization, distillation, compression, inference optimization, etc.)
Experience with open‑source frameworks for model customization like trl, verl, and for building LLM‑powered applications like LangChain, LlamaIndex and/ or similar tools
Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non‑experts
Demonstrated ability to identify and frame technical problems from broad product‑level and business‑level problem areas
Track record of leading the design, implementation and delivery of scientifically complex solutions that span multiple teams
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, including support for the interview or onboarding 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.
Posted: November 29, 2025 (Updated 2 days ago)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.
#J-18808-Ljbffr
Amazon launched the Generative AI Innovation Center (GAIIC) in June 2023 to help AWS customers accelerate the use of Generative AI to solve business and operational problems and promote innovation in their organization (https://press.aboutamazon.com/2023/6/aws-announces-generative-ai-innovation-center).
GAIIC provides opportunities to innovate in a fast‑paced organization that contributes to game‑changing projects and technologies that get deployed on devices and in the cloud.
Key job responsibilities: As an Applied Science Manager in GAIIC, you’ll partner with technology and business teams to build new GenAI solutions that delight our customers. You will be responsible for directing a team of data/research/applied scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, and deliver state‑of‑the‑art solutions to customers’ business and mission problems. Your team will be working with terabytes of text, images and other types of data to address real‑world problems.
The successful candidate will possess both technical and customer‑facing skills that will allow you to be the technical “face” of AWS within our solution‑providers’ ecosystem/environment as well as directly to end customers. You will drive discussions with senior technical and management personnel within customers and partners, and provide the technical background that enables them to interact with and give guidance to data/research/applied scientists and software developers.
The ideal candidate will also have a demonstrated ability to think strategically about business, product and technical issues. Finally, of critical importance, the candidate will be an excellent technical team manager, someone who knows how to hire, develop and retain high‑quality technical talent.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption and growth from the largest and fastest‑growing small‑ and mid‑market accounts to enterprise‑level customers including the public sector. The AWS Global Support team interacts with leading companies and believes that world‑class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission‑critical applications on top of AWS services.
About the team: AWS Global Services includes experts from across AWS who help our customers design, build, operate and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in this job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?: Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture: AWS values curiosity and connection. Our employee‑led and company‑sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by bold ideas, fresh perspectives and passionate voices our teams bring to everything we do.
Mentorship & Career Growth: We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge‑sharing, mentorship and other career‑advancing resources here to help you develop into a better‑rounded professional.
Work/Life Balance: We value work‑life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
Basic Qualifications
Japanese fluency, Business English
PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field plus 5 years of relevant experience; or Master’s degree plus 10 years of relevant work experience
5+ years of hands‑on experience with Python to build, train and evaluate models
5+ 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
2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post‑training, continual pre‑training, fine‑tuning or reinforcement learning techniques
Scientific publication track record at top‑tier AI/ML/NLP conferences or journals
Experience directly managing scientists or machine learning engineers
Preferred Qualifications
Demonstrated experience with building LLM‑powered agentic workflow, orchestration and agent customization
Experience with model optimization techniques (quantization, distillation, compression, inference optimization, etc.)
Experience with open‑source frameworks for model customization like trl, verl, and for building LLM‑powered applications like LangChain, LlamaIndex and/ or similar tools
Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non‑experts
Demonstrated ability to identify and frame technical problems from broad product‑level and business‑level problem areas
Track record of leading the design, implementation and delivery of scientifically complex solutions that span multiple teams
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, including support for the interview or onboarding 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.
Posted: November 29, 2025 (Updated 2 days ago)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability or other legally protected status.
#J-18808-Ljbffr