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Applied Science Manager, AWS Generative AI Innovation Center

Amazon (AI roles) · Lisbon, PRT

No salary listed. Estimated from 440 salary-disclosed Operations roles on this board: $152K–$225K (interquartile range; estimate, not the employer's figure).

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About the role
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. The candidate must ne be able to drive discussions with senior technical and management personnel within customers and partners while hacing technical background that enables them to interact with and give guidance to AI scientists/engineers 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.

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/solutions/products 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 GenAI Innovation Center helps customers define and execute AI Strategy, scope and develop use cases that will create the greatest value for their businesses, select/develop/customise/fine-tune the right models, define paths to navigate technical or business challenges, and make plans for launching solutions at scale, responsibly and cost efficiently - PhD in Computer Science (CS), Computer Engineering (CE), or related technical field. Or MSc plus several years of industry experience
- Experience of building, managing, and scaling AI/ML teams of AI Scientists and Engineers
- Deep Machine learning/AI/ GenAI knowledge
- Ability to demonstrate senior stakeholder management skills and collaborate effectively with multidisciplinary teams.
- 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.
- Ability to translate informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience building and delivering machine learning models or developing algorithms for business application
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