Amazon
Sr GenAI Specialist Solutions Architect, Amazon SageMaker
Amazon, New York, New York, us, 10261
Sr GenAI Specialist Solutions Architect, Amazon SageMaker
Job ID: 2762281 | Amazon Web Services, Inc.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) API-driven Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call.AWS is looking for a GenAI/ML Solutions Architect (GenAI/ML SA), who will be the Subject Matter Expert (SME) for helping customers worldwide design solutions that leverage our ML services. This role will specifically specialize in using state-of-the-art techniques to pre-train and fine-tune foundation models. 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, specifically in advanced generative AI technologies. A strong mathematics and statistics background is preferred in addition to experience fine-tuning foundation 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.If you are a qualified and accepted candidate, you may work out of any of the following cities: Seattle, San Francisco, Silicon Valley, New York, Arlington. Travel up to 50% across the AMERICAs may be possible.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 worldwide 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 worldwide.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- 10+ years of IT development or implementation/consulting in the software or Internet industries experiencePREFERRED QUALIFICATIONS
- 5+ years of infrastructure architecture, database architecture and networking experience- Experience working with end user or developer communitiesAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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Job ID: 2762281 | Amazon Web Services, Inc.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) API-driven Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call.AWS is looking for a GenAI/ML Solutions Architect (GenAI/ML SA), who will be the Subject Matter Expert (SME) for helping customers worldwide design solutions that leverage our ML services. This role will specifically specialize in using state-of-the-art techniques to pre-train and fine-tune foundation models. 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, specifically in advanced generative AI technologies. A strong mathematics and statistics background is preferred in addition to experience fine-tuning foundation 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.If you are a qualified and accepted candidate, you may work out of any of the following cities: Seattle, San Francisco, Silicon Valley, New York, Arlington. Travel up to 50% across the AMERICAs may be possible.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 worldwide 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 worldwide.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- 10+ years of IT development or implementation/consulting in the software or Internet industries experiencePREFERRED QUALIFICATIONS
- 5+ years of infrastructure architecture, database architecture and networking experience- Experience working with end user or developer communitiesAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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