Sr. Specialist SA - AI/ML

Job summary
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.

In this role, your creativity will link technology to tangible solutions, with the opportunity to define cloud-native Machine Learning reference architectures for a variety of use cases.
You 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).
If you can educate AWS customers about the art of the possible, while challenging the impossible, come build the future with us.



About the team
About Us

Inclusive Team Culture

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance

Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

Basic Qualifications

· Background in any of the following: Cloud Architecture, DevOps, Software Development, Infrastructure Architecture, ML Engineering or Data Science
· In-depth working knowledge and experience of the Artificial Intelligence/Machine Learning technical domain.
· Technical Degree (Computer Science, Maths, Engineering or equivalent) and/or relevant tech experience.
· A passion for technology and for learning.

Preferred Qualifications

The following qualifications are desired but not required:
· Experience designing, building, refactoring or operating Machine Learning solutions - either on premises or in the cloud
· Working knowledge of cloud native architectures
· Knowledge of a Python and/or scripting, Infrastructure as Code etc.
· In-depth working knowledge of DevOps, Serverless, Big Data and Analytics technologies.
· Experience working in a customer-facing role or a role which involved public speaking
· AWS certification (e.g. AWS Solutions Architect Associate or Professional) or other industry certification
· AWS Certified Machine Learning – Specialty



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