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 comprehensive 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 GenerativeAI? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/GenAI 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 layers of the AI stack: 1) API-driven Inference Services like Amazon Bedrock 2) Agentic AI including Agentic platforms, tool usage, evaluations, governance and cost management along with use of Agentic SDKs such as Strands and platforms such as Amazon Bedrock AgentCore 3) Frameworks and Infrastructure with tools like Pytorch and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, k to quickly add intelligence to applications with simple API calls.
AWS is looking for a Machine Learning Solutions Architect (ML SA), who will be the Subject Matter Expert (SME) for helping customers in the AMERICAS design solutions that leverage our ML services. As part of the team, you will work closely with ISV(Independent Software Vendors) 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 Generative AI, 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 GenAI space, and will leverage this knowledge to help AWS customers in their selection process.
If you are a qualified and accepted candidate, you may work out of any of the following cities: San Jose, Los Angeles, Denver, Chicago, Austin, Dallas, Atlanta, Arlington.
Travel up to 50% across the USA may be possible.
Key job responsibilities
Working with customers’ development and data science teams to deeply understand their business and technical needs. After understanding their needs, you will design solutions that make the best use of the AWS cloud platform and AWS AI/ML Services including SageMaker, Amazon Bedrock, Amazon AgentCore, Amazon Rekognition, Amazon Transcribe, Amazon Quick, Amazon Personalize, and other AI/ML services.
- Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment in the AMERICAS for Amazon SageMaker and related services that support GenAI use cases.
- Thought Leadership – Evangelize AWS ML services and share best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
- Act as a technical liaison between customers and the AWS SageMaker or other service teams to provide customer driven product improvement feedback.
- Develop and support an AWS internal community of GenAI related subject matter experts in the AMERICAS.
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.
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