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Job Description
AWS is looking for a self-driven Machine Learning Solutions Architect (ML SA), who will be the Subject Matter Expert (SME) for helping customers in the MENA/SA design solutions that leverage our ML services. As part of the team, you will work closely with customers to enable large-scale use cases, design ML pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage AI/ML on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward.
You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building complex machine learning models. You will be familiar with the ecosystem of software vendors in the AI/ML space, and will leverage this knowledge to help AWS customers in their selection process.
Key job responsibilities
Thought Leadership Evangelize AWS ML services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment in the MENA/SA for Amazon SageMaker.
Act as a technical liaison between customers and the AWS SageMaker services teams to provide customer driven product improvement feedback.
Develop and support an AWS internal community of ML related subject matter experts in the MENA/SA.
About the team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and were 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.
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazons culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we arent focused on how many hours you spend at work or online. Instead, were happy to offer a flexible schedule so you can have a more productive and well-balanced lifeboth in and outside of work
BASIC QUALIFICATIONS 8 years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
3 years of design, implementation, or consulting in applications and infrastructures experience
PREFERRED QUALIFICATIONS You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building complex machine learning models. You will be familiar with the ecosystem of software vendors in the AI/ML space, and will leverage this knowledge to help AWS customers in their selection process.
