Senior Deep Learning Architect, Generative AI

Job Overview

The Generative AI Innovation Center at AWS is seeking a Senior Deep Learning Architect to join our team. This role is pivotal in helping AWS customers accelerate the use of Generative AI and realize transformational business opportunities. You will be part of a cross-functional team of ML scientists, engineers, architects, and strategists working closely with customers to build bespoke solutions that harness the power of generative AI.

Key Responsibilities

• Collaborate with ML Scientists and Engineers: Research, design, and develop cutting-edge generative AI algorithms to address real-world challenges.
• Customer Engagement: Work directly with customers to understand their business problems and aid them in implementing generative AI solutions. Deliver briefings and deep dive sessions to guide customers on adoption patterns and paths for generative AI.
• Technical Asset Creation: Create and deliver reusable technical assets that help accelerate the adoption of generative AI on the AWS platform.
• Best Practices and Recommendations: Develop and share best practice recommendations, tutorials, blog posts, sample code, and presentations tailored to technical, business, and executive stakeholders.
• Feedback and Product Development: Provide customer and market feedback to Product and Engineering teams to help define product direction.

About the Team

The Generative AI Innovation Center pairs you with AWS science and strategy experts with deep experience in AI/ML and generative AI techniques. The team focuses on imagining new applications of generative AI, identifying new use cases based on business value, and integrating generative AI into existing applications and workflows.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and continue to innovate, which is 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

At AWS, we 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 (gender diversity) conferences, inspire us to embrace our uniqueness.

Mentorship & Career Growth

We are committed to raising our performance bar and becoming Earth’s Best Employer. You’ll find endless knowledge-sharing, mentorship, and other career-advancing resources here to help you develop into a well-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.

Basic Qualifications

• Several years of experience in design, implementation, or consulting in applications and infrastructures.
• Bachelor’s degree in computer science, engineering, mathematics, or equivalent experience.
• Experience architecting or deploying Cloud/Virtualization solutions in enterprise customers.
• Proven knowledge of deep learning and experience hosting and deploying ML solutions.

Preferred Qualifications

• 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.

AWS is an equal opportunity employer. We value diverse experiences and encourage candidates to apply, even if they do not meet all of the qualifications and skills listed in the job description.