Sr. AI/ML Specialist SA, AGS EU North at Amazon
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AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
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) for our Europe North customers? 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) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition 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 Europe North (BeNeLux, Denmark, Sweden, Norway, Finland, Iceland, Estonia, Latvia, Lithuania) design solutions that leverage our GenAI services, including Amazon Bedrock, Amazon SageMaker, and Amazon Q. As part of the team, you will work closely with customers to enable large-scale use cases, design GenAI 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 GenAI 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 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.
Key job responsibilities
The Europe North AI/ML Specialist SA team builds 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 while adopting Machine Learning across their organization.
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 with regard to their usage of our services impacting 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 architectural patterns 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 want to educate AWS customers about the art of the possible, while challenging the impossible, come build the future with us.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
We are open to hiring candidates to work out of one of the following locations:
Stockholm, SWE
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) for our Europe North customers? 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) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition 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 Europe North (BeNeLux, Denmark, Sweden, Norway, Finland, Iceland, Estonia, Latvia, Lithuania) design solutions that leverage our GenAI services, including Amazon Bedrock, Amazon SageMaker, and Amazon Q. As part of the team, you will work closely with customers to enable large-scale use cases, design GenAI 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 GenAI 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 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.
Key job responsibilities
The Europe North AI/ML Specialist SA team builds 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 while adopting Machine Learning across their organization.
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 with regard to their usage of our services impacting 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 architectural patterns 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 want to educate AWS customers about the art of the possible, while challenging the impossible, come build the future with us.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
We are open to hiring candidates to work out of one of the following locations:
Stockholm, SWE