Amazon Senior Deep Learning Architect AWS Generative AI Innovation Center 

United Kingdom, England, London 

359774812

As a Senior 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.Key job responsibilities- Create and deliver reusable technical assets that help to accelerate the adoption of generative AI on AWS platformDiverse 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.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

- Several years of experience in design, implementation, or consulting in applications and infrastructures
- Bachelor’s degree in computer science, engineering, mathematics or equivalent, or experience in a professional field or military
- Experience architecting or deploying Cloud/Virtualization solutions in enterprise customers
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences)

- Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models
- Proven knowledge of AWS platform and tools
- Hands-on experience of building ML solutions on AWS
- Experience in professional software development
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field