Applied Science Manager, Generative AI Innovation Center, AWS

Applied Science Manager, Generative AI Innovation Center, AWS Job ID: | Amazon Web Services Japan GKAmazon 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 ( 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 ResponsibilitiesPartner with technology and business teams to build new GenAI solutions that delight our customers.Direct a team of data/research/applied scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, delivering state-of-the-art solutions to customer’s business and mission problems.Work with terabytes of text, images, and other types of data to address real-world problems.Act as the technical “face” of AWS within our solution providers’ ecosystem and directly to end customers, driving discussions with senior technical and management personnel.Provide technical guidance to data/research/applied scientists and software developers.Think strategically about business, product, and technical issues.Serve as an excellent technical team manager, hiring, developing, and retaining high quality technical talent.The successful candidate will possess both technical and customer-facing skills that allow them to be the technical “face” of AWS within our solution providers’ ecosystem and to directly engage end customers.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 the 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 the 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 QualificationsJapanese fluency, Business EnglishPhD 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 experience5+ years of hands on experience with Python to build, train, and evaluate models5+ years of experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing2+ 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 journalsExperience directly managing scientists or machine learning engineersPreferred QualificationsDemonstrated experience with building LLM-powered agentic workflow, orchestration, and agent customizationExperience 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 toolsStrong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-expertsDemonstrated 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.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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.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