AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and unwavering support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow.
Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools on Amazon Web Service (AWS)? Come join us!
At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.
Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) Generative AI Services like Amazon Bedrock and Amazon Q to build GenAI powered applications.
AWS is looking for a Machine Learning Solutions Architect (ML SA), who will be the Subject Matter Expert (SME) for helping Restaurants, Retail and Consumer Packaged Goods (RRCG) customers 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
- Provide customers with deep technical expertise in Generative AI, Traditional AI, and Machine Learning with AWS products to meet their business objectives.
- Collaborate with specialist, sales, marketing, and products teams to ideate around your customers’ most challenging problems.
- Act as a trusted advisor to line of business, AI, Data, and C-suite leaders.
- Lead architectural reviews and workshops to advance your customer’s technical objectives.
- Act as a thought leader sharing best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re: Invent, etc. Participate as a leader in AWS technical communities.
- Educate customers on the value proposition of AWS, and participate in architectural discussions to ensure solutions are designed for successful deployment in the cloud.
- Provide data and anecdotes on what is working and what is not back to the larger specialist community and product teams. Act as primary point of contact for urgent customer issues in your technical specialty.
- Thought Leadership and External Representation: Serve as a thought leader in the Generative AI space, representing AWS at industry events and conferences, such as AWS re:Invent.
- Develop technical content, workshops, and thought leadership to enable the broader technical community, including Solution Architects, Data Scientists, and Technical Field Community members.
- We prefer this candidate to have a track record of thought leadership and innovation around Machine Learning, Comfortable presenting to senior data and AI leaders, and have demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment.
About the team
Diverse Experiences
AWS 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?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
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
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
