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Science manager, model customization, generative ai innovation center

London
Amazon
Science
Posted: 6 October
Offer description

Job ID: 3076889 | AWS EMEA SARL (UK Branch)

Amazon launched the Generative AI Innovation Center (GenAIIC) in Jun 2023 to help AWS customers accelerate the use of Generative AI to solve business and operational problems and promote innovation in their organization. Starting in 2024, the Innovation Center launched a new Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop and optimize models to power their solutions, 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.

The 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 a Data Science Manager in GenAIIC, 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 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. Your team will be working with terabytes of text, images, and other types of data to address real-world problems.


Responsibilities

* Be the technical “face” of AWS within our solution providers’ ecosystem/environment as well as directly to end customers, and drive discussions with senior technical and management personnel.
* Guide data/research/applied scientists and software developers with the technical background to interact with and provide direction to the team.
* Think strategically about business, product, and technical issues, and demonstrate strong people management skills to hire, develop, and retain high-quality technical talent.
* Collaborate with AWS Sales, Marketing, and Global Services (SMGS) and AWS Global Support teams to drive revenue, adoption, and growth across customer segments.
* Lead a team of scientists, deep learning architects, and ML engineers to build generative AI models and data pipelines and deliver state-of-the-art solutions to customer problems.


Basic Qualifications

* PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field
* Knowledge of Python or R or other scripting language
* Experience in building quantitative solutions as a scientist or science manager
* Experience directly managing scientists or machine learning engineers
* Experience in applying statistical models for large-scale applications and building automated analytical systems


Preferred Qualifications

* Experience in at least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
* Experience with fairness in machine learning and AI to detect and remove bias in ML/AI systems
* Bachelor's degree in Computer Science or equivalent

Amazon is an equal opportunities employer. We believe that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding priority. Please consult our Privacy Notice to know more about how we collect, use and transfer personal data of our candidates.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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 our accommodations information page for more details. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

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