Amazon Web Services (AWS)
Senior Data Scientist, AWS Professional Services
Amazon Web Services (AWS), Arlington, Virginia, United States, 22201
Overview
Senior Data Scientist, AWS Professional Services. This role involves applying AI/ML solutions for real-world business challenges within AWS ProServe, partnering with customers to design, implement, and scale AI/ML initiatives, and ensuring responsible and cost-efficient use of AI. Responsibilities
Lead end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI algorithms and build ML systems and operations (MLOps) using AWS services to address real-world challenges Interact with customers directly to understand the business challenges, deliver briefing and deep dive sessions to customers and guide them on adoption patterns and paths to production Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations tailored to technical, business, and executive stakeholders Provide customer and market feedback to product and engineering teams to help define product direction This is a customer-facing role with potential travel to customer sites as needed. About the Team
ABOUT AWS: Diverse Experiences. Amazon values diverse experiences. If you do not meet all of the preferred qualifications, we encourage you to apply. Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. Basic Qualifications
Master's degree in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field with 5+ years of experience; or bachelor's degree with 8+ years of experience 5+ years of building machine learning models for business application experience 3+ years of hands-on experience with training, fine-tuning, evaluating, and deploying transformer models in production Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications Experience with technical customer-facing engagements, and strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts Preferred Qualifications
PhD in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field AWS experience preferred, with proficiency in AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, VPC) and professional certifications 2+ years of experience with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, and/ or similar tools 5+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch or TensorFlow Experience in launching AI applications in production on AWS Experience building ML pipelines with MLOps best practices, including: data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; experience with container and CI/CD pipelines Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit the AWS accommodations page for more information. For more information, please visit https://amazon.jobs/content/en/how-we-hire/accommodations. This position will remain posted until filled. Applicants should apply via our internal or external career site. Company - Amazon Web Services, Inc. Job ID: A3087563
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Senior Data Scientist, AWS Professional Services. This role involves applying AI/ML solutions for real-world business challenges within AWS ProServe, partnering with customers to design, implement, and scale AI/ML initiatives, and ensuring responsible and cost-efficient use of AI. Responsibilities
Lead end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI algorithms and build ML systems and operations (MLOps) using AWS services to address real-world challenges Interact with customers directly to understand the business challenges, deliver briefing and deep dive sessions to customers and guide them on adoption patterns and paths to production Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations tailored to technical, business, and executive stakeholders Provide customer and market feedback to product and engineering teams to help define product direction This is a customer-facing role with potential travel to customer sites as needed. About the Team
ABOUT AWS: Diverse Experiences. Amazon values diverse experiences. If you do not meet all of the preferred qualifications, we encourage you to apply. Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. Basic Qualifications
Master's degree in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field with 5+ years of experience; or bachelor's degree with 8+ years of experience 5+ years of building machine learning models for business application experience 3+ years of hands-on experience with training, fine-tuning, evaluating, and deploying transformer models in production Experience with cloud services related to machine learning (e.g., Amazon SageMaker) and generative AI applications Experience with technical customer-facing engagements, and strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts Preferred Qualifications
PhD in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field AWS experience preferred, with proficiency in AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, VPC) and professional certifications 2+ years of experience with design, deployment, and evaluation of AI agents and orchestration approaches; experience with open source frameworks like LangChain, LangGraph, LlamaIndex, and/ or similar tools 5+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience using PyTorch or TensorFlow Experience in launching AI applications in production on AWS Experience building ML pipelines with MLOps best practices, including: data preprocessing, distributed & GPU training, model deployment, monitoring, and retraining; experience with container and CI/CD pipelines Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit the AWS accommodations page for more information. For more information, please visit https://amazon.jobs/content/en/how-we-hire/accommodations. This position will remain posted until filled. Applicants should apply via our internal or external career site. Company - Amazon Web Services, Inc. Job ID: A3087563
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