Senior Data Scientist, Model Customization, Generative AI Innovation Center, Model Customization

Overview

The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative 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 Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.

Key responsibilities

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
• Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
• Provide customer and market feedback to product and engineering teams to help define product direction

About the team and culture

AWS values diverse experiences. If you do not meet all of the qualifications listed, we encourage you 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.

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 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. You’ll find knowledge-sharing, mentorship and other career-advancing resources to help you develop into a well-rounded professional.

Work/Life Balance

We value work-life harmony with flexibility as part of our working culture, supporting you at work and at home.

Basic Qualifications

- Bachelor’s degree and 8 years of experience or Master’s degree and 4 years of experience
- 2+ years of hands-on experience with generative AI technology
- 5+ years of experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing, neural deep learning methods and/or machine learning
- 5+ years of hands-on experience with Python to build, train, and evaluate models
- 4+ years of technical client engagement experience

Preferred Qualifications

- Master’s or PhD in computer science, engineering, mathematics, operations research, or a highly quantitative field
- Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
- Experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches
- Experience with design, development, and optimization of high-quality prompts and templates that guide LLM behavior
- Experience with open source frameworks for building LLM-powered applications like LangChain, LlamaIndex, or similar tools
- Hands-on experience building cloud applications

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect, use and transfer personal data of our candidates.

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 accommodations page for more information.