Applied Science Manager, Generative AI Innovation Center, AWS

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 (

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 youll 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 be able to drive discussions with senior technical and management personnel within customers and partners as well as 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 and 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 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. Youll 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 hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats 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
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
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- 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 Masters 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

- 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.

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