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

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? 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.

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• 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
  

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.

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.

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.

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.

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we 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.

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• 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 any of the following areas: 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
  

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• Masters or PhD degree in computer science, engineering, mathematics, operations research, or in 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 the behavior and responses of LLMs
  
• Experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/or similar tools
  
• Hands‑on experience building cloud applications