Data Science Manager, Model Customization, Generative AI Innovation Center at Amazon SZ South 3 GmbH

Arlington, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Dec, 25

Salary

272400.0

Posted On

19 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Deep Learning, NLP, Information Retrieval, Analytics, Model Customization, Generative AI, Technical Management, Customer Engagement, Strategic Thinking, Team Development, Software Development, Algorithm Development, Cloud Computing, Problem Solving

Industry

Software Development

Description

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 (https://press.aboutamazon.com/2023/6/aws-announces-generative-ai-innovation-center). 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. 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 About the team 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 Qualifications: - 3+ years of scientists or machine learning engineers management experience - Knowledge of ML, NLP, Information Retrieval and Analytics - Experience directly managing scientists or machine learning engineers - Quantitative Masters Degree or Quantitative Bachelors Degree Preferred Qualifications: - Experience building machine learning models or developing algorithms for business application - Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers - PhD degree in quantitative field 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 https://amazon.jobs/content/en/how-we-hire/accommodations [https://amazon.jobs/content/en/how-we-hire/accommodations] for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $142,300/year in our lowest geographic market up to $272,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits [https://www.aboutamazon.com/workplace/employee-benefits]. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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Responsibilities

As a Data Science Manager, you will lead a team to build generative AI models and pipelines, delivering innovative solutions to customer challenges. You will collaborate with technology and business teams to create customized generative AI solutions that drive value for customers.