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Amazon

Deep Learning Architect, Generative AI Innovation Center

location icon US, CA, San Diego
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Artificial Intelligence (AI) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.

The Generative AI Innovation Center team within AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and the cloud. As a Deep Learning Architect, you'll partner with technology and business teams to build new services that surprise and delight our customers. You will be working with terabytes of text, images, and other types of data to solve real-world problems.

We’re looking for top architects, system and software engineers capable of using ML, Deep Learning, Generative AI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

Sales, Marketing and Global Services (SMGS)

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
In this role, you will:
• Use Deep Learning models and Generative AI tools, such as Amazon SageMaker and Amazon Bedrock, to provide a scalable cloud environment for our customers to label data, build, train, tune and deploy their models
• Collaborate with our applied and data scientists to create scalable Generative AI solutions for business problems
• Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem
• Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes
• Work closely with account teams, applied/data scientist teams, and product engineering teams to drive model implementations and new algorithms


A day in the life
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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
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 & 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 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.

We are open to hiring candidates to work out of one of the following locations:

Austin, TX, USA | New York, NJ, USA | San Diego, CA, USA | San Francisco, CA, USA | Santa Clara, CA, USA | Seattle, WA, USA
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Publication date: 2024-03-03
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