Amazon
Senior Data Scientist, AWS Professional Services
Amazon, Nashville, Tennessee, United States, 37247
Senior Data Scientist, AWS Professional Services
Job ID: 3087563 | Amazon Web Services, Inc.
Are you looking to work at the forefront of Machine Learning (ML) and Artificial Intelligence (AI)? Would you be excited to apply AI algorithms to solve real world problems with significant impact? The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Senior Data Scientist to help customers implement AI/ML solutions and realize transformational business opportunities.
This is a team of scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of AI. The team helps customers imagine and scope use cases that will create the greatest value for their businesses, select and train and fine-tune the right models, define paths to navigate technical or business challenges, develop scalable solutions and applications, and launch them in production. The team provides guidance and implements best practices for applying AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
We’re looking for Senior Data Scientists capable of using AI/ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
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, and guide 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. 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 startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance. We value work-life harmony and 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 in the cloud.
Inclusive Team Culture. We learn and are curious. Our employee-led affinity groups foster a culture of inclusion and ongoing events and learning experiences to embrace our differences.
Mentorship and Career Growth. We provide knowledge-sharing, mentorship, and career-advancing resources to help you develop professionally.
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 applications
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 to non-experts
Preferred Qualifications
PhD in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
AWS experience and 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
5+ years of deep learning, computer vision, human-robotic interaction, or related algorithms experience using PyTorch or TensorFlow
Experience 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, please review our procedures for accommodations in the hiring process.
#J-18808-Ljbffr
Are you looking to work at the forefront of Machine Learning (ML) and Artificial Intelligence (AI)? Would you be excited to apply AI algorithms to solve real world problems with significant impact? The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Senior Data Scientist to help customers implement AI/ML solutions and realize transformational business opportunities.
This is a team of scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of AI. The team helps customers imagine and scope use cases that will create the greatest value for their businesses, select and train and fine-tune the right models, define paths to navigate technical or business challenges, develop scalable solutions and applications, and launch them in production. The team provides guidance and implements best practices for applying AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
We’re looking for Senior Data Scientists capable of using AI/ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
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, and guide 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. 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 startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance. We value work-life harmony and 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 in the cloud.
Inclusive Team Culture. We learn and are curious. Our employee-led affinity groups foster a culture of inclusion and ongoing events and learning experiences to embrace our differences.
Mentorship and Career Growth. We provide knowledge-sharing, mentorship, and career-advancing resources to help you develop professionally.
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 applications
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 to non-experts
Preferred Qualifications
PhD in computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
AWS experience and 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
5+ years of deep learning, computer vision, human-robotic interaction, or related algorithms experience using PyTorch or TensorFlow
Experience 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, please review our procedures for accommodations in the hiring process.
#J-18808-Ljbffr