Senior Deep Learning Architect

vor 3 Wochen


Berlin, Berlin, Deutschland AWS EMEA SARL (Germany Branch) Vollzeit

The AWS Generative AI Innovation Center supports customers in accelerating the adoption of Generative AI and achieving transformative business outcomes.

This cross-functional team of ML scientists, engineers, and architects collaborates closely with customers to develop tailored solutions that leverage the power of Generative AI.

As a Senior Deep Learning Architect, you will work closely with technology and business teams to design and implement cutting-edge solutions that exceed customer expectations.

You will be part of a fast-paced organization that drives innovation and contributes to groundbreaking projects and technologies.

We are seeking experienced professionals who can utilize Generative AI and other ML techniques to create, evangelize, and implement state-of-the-art solutions for complex problems.

AWS Sales, Marketing, and Global Services (SMGS) drives revenue, adoption, and growth from small- to enterprise-level customers, including public sector.

AWS Global Support interacts with leading companies and prioritizes world-class support as essential to customer success.

AWS Support partners with global customers building mission-critical applications on top of AWS services.

Key Responsibilities
  • Collaborate with ML scientists and engineers to research, design, and develop innovative Generative AI algorithms addressing real-world challenges.
  • Work across customer engagements to identify and share successful Generative AI adoption patterns with teams and leadership.
  • Interact with customers to understand business needs, provide implementation guidance, and deliver briefing and deep dive sessions.
  • Create and deliver reusable technical assets accelerating Generative AI adoption on the AWS platform.
  • Develop and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations for technical and business stakeholders.
  • Provide customer and market feedback to Product and Engineering teams to inform product direction.


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