Overview

The Generative AI Innovation Center at AWS helps AWS customers accelerate the use of Generative AI and realize transformational business opportunities. This is a cross-functional team of ML scientists, engineers, architects, and strategists working step-by-step with customers to build bespoke solutions that harness the power of generative AI.

As a Deep Learning Architect, you'll partner with technology and business teams to build solutions that surprise and delight our customers. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.

We're looking for Engineers and Architects capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

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.

Responsibilities

• Collaborate with ML scientists and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges
• Work across customer engagements to understand adoption patterns for generative AI and rapidly share them across teams and leadership
• Interact with customers directly to understand the business problem, assist in the implementation of generative AI solutions, deliver briefing and deep-dive sessions, and guide customers on adoption patterns and productionization paths for generative AI
• Create and deliver reusable technical assets that help to accelerate the adoption of generative AI on the AWS platform
• Create and deliver best-practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders
• Provide customer and market feedback to Product and Engineering teams to help define product direction

About the team

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 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.

Diversity and Inclusion

AWS values diverse experiences. If you do not meet all of the qualifications and skills listed, 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 continue innovating. Customers from startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Our employee-led affinity groups foster a culture of inclusion that empowers us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to embrace our uniqueness.

Mentorship & Career Growth

We continuously raise the performance bar as we strive to become Earth's Best Employer. You'll find knowledge-sharing, mentorship, and other career-advancing resources to help you develop into a well-rounded professional.

Work/Life Balance

We value work-life harmony and strive for flexibility as part of our working culture. When we feel supported at work and home, we can achieve more in the cloud.

BASIC QUALIFICATIONS

• Bachelor's degree in computer science, engineering, mathematics or equivalent
• Experience in design, implementation, or consulting in applications and infrastructures
• Experience architecting or deploying Cloud/Virtualization solutions in enterprise customers
• Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences)
• Scientific thinking and the ability to invent, with a track record of thought leadership and contributions that have advanced the field

PREFERRED QUALIFICATIONS

• MSc degree in computer science, engineering, mathematics or equivalent
• Proven knowledge of Generative AI and hands-on experience building applications with large foundation models
• Proven knowledge of AWS platform and tools
• Hands-on experience building ML solutions on AWS
• Experience in professional software development

Amazon is an equal opportunities employer. We believe passionately 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 top priority for Amazon. Please consult our Privacy Notice to know more about how we collect, use and transfer the 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 the accommodations page for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.