Amazon Sr Specialist SA - AI/ML Public Sector UK PS 

United Kingdom, England, London 

18459812

As a Specialist ML Solutions Architect at AWS, you’ll build technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey in adopting Machine Learning across their organisation.
You’ll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging Machine Learning projects.
Internally, you will be the voice of the customer, sharing their needs and wants to inform the roadmap of AWS AI/ML features.
Key job responsibilitiesYou will participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts) and evangelize and educate about running Machine Learning workloads on AWS technology (e.g. through workshops, user groups, meetups, public speaking, online videos or conferences).
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred 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
Work/Life BalanceMentorship and 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.

- Bachelor's degree in computer science, engineering, mathematics or equivalent, or experience in a professional field or military
- Experience in IT development or implementation/consulting in the software or Internet industries
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- ML Engineering or Data Science and In-depth working knowledge and experience of the Artificial Intelligence / Machine Learning technical domain.