Applied Science Manager, AWS Generative AI Innovation Center

Amazon launched the Generative AI Innovation Center (GenAIIC) 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).

GenAIIC 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. As an Applied Science Manager in GenAIIC, you'll partner with technology and business teams to build new generative AI 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 customer’s business and mission 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. 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.

Key job responsibilities
You will work directly with customers to drive adoption and shape the future of the most exciting emerging technology by understanding the business problem and guiding our customers in implementation of generative AI solutions, and developing long-term strategic relationships with key accounts

You will help develop the industry’s best generative AI delivery team by enabling and coaching your specialist team on best practices and how to create and present value-driven architectures of widely varying size and complexity. You will grow an existing team by hiring, on-boarding, training, and developing new Scientists, Architects, and Engineers from internal and external sources.

You will identify opportunities for building reusable technical assets based on recurring patterns of customer needs

You will provide customer and market feedback to Product and Engineering teams to help define product direction

You will drive revenue growth across a broad set of customers

You will be a thought leader and drive value creation for our customers, shaping technical solutions, growing the team, and leading specific customer engagements

You will deliver briefing and deep dive sessions to customers and guide customers on adoption patterns and paths to production

About the team
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and fine-tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.

Diverse Experiences
Amazon 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.
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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship and 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.

<br/><b>QUALIFICATIONS DE BASE</b><br/>- PhD in Computer Science (CS), Computer Engineering (CE), or related technical field. Or MSc plus several years of industry experience<br/><br/>- Several years of scientists or machine learning engineers management experience and knowledge of ML, NLP, Information Retrieval and Analytics <br/><br/>- Ability to demonstrate senior stakeholder management skills and collaborate effectively with multidisciplinary teams.<br/><br/>- Experience directly managing scientists or machine learning engineers <br/><br/>- Ability to translate informal customer requirements into problem definitions, dealing with ambiguity and competing objectives<br/><b>QUALIFICATIONS APPRÉCIÉES</b><br/>- Experience building machine learning models or developing algorithms for business application<br/><br/>- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers <br/><br/>- Deep expertise in generative AI and hands on experience of deploying and hosting Large Foundational Models<br/><br/>- Experience and deep knowledge of AWS and AWS AI/ML services<br/><br/>- Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences. <br/><br/>- Project management experience working on cross-functional projects<br/><br/>Amazon est un employeur engagé pour l'égalité des chances. Nous sommes convaincus qu'une main d'oeuvre diversifée est essentielle à notre réussite. Nous prenons nos décisions de recrutement en fonction de votre expérience et de vos compétences. Nous apprécions votre envie de découvrir, d'inventer, de simplifier et de construire. La protection de votre vie privée et la sécurité de vos données constituent depuis longtemps une priorité absolue pour Amazon. Veuillez consulter notre Politique de Confidentialité pour en savoir plus sur la façon dont nous collectons, utilisons et traitons les données personnelles de nos candidats.