Join the Generative AI Innovation Center at AWS

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

The Generative AI Innovation Center at AWS is a strategic team helping customers implement Generative AI solutions and realize transformational business opportunities. This team comprises strategists, data scientists, engineers, and solution architects working with customers to build bespoke solutions harnessing the power of generative AI.

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 to optimize risk, profitability, and customer experience.

Key Job Responsibilities

As an ML Data Scientist, you will:

• Collaborate with ML scientists and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms for real-world challenges.
• Interact with customers to understand business problems, assist in the implementation of generative AI solutions, and deliver sessions to guide customer adoption.
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations for various stakeholders.
• Provide feedback to Product and Engineering teams to help define product direction.

About the Team

The team assists customers in imagining and scoping use cases that create the greatest value for their businesses, selecting and training models, developing proof-of-concepts, and launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost-efficiently.

Diverse Experiences

Amazon values diverse experiences. Even if you do not meet all the preferred qualifications and skills listed in the job description, we encourage candidates to apply. Do not let non-traditional career paths or alternative experiences stop you from applying.

Why AWS

Amazon Web Services (AWS) is the world’s most comprehensive cloud platform. We pioneered cloud computing and never stopped innovating, which is why customers from startups to Global 500 companies trust our robust products and services to power their businesses.

Work/Life Balance

We value work-life harmony. Success at work should not come at the expense of home life. Flexible work hours and arrangements are part of our culture, supporting us both in the workplace and at home.

Inclusive Team Culture

At AWS, we embrace learning and curiosity. Employee-led affinity groups foster a culture of inclusion, empowering us to be proud of our differences. Events like Conversations on Race and Ethnicity (CORE) and AmazeCon inspire us to embrace our uniqueness.

Mentorship and Career Growth

We strive to become Earth’s Best Employer by sharing knowledge and resources, fostering mentorship, and providing career-advancing opportunities.

Basic Qualifications

• Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
• Relevant experience in building large-scale machine learning or deep learning models.
• Experience communicating across technical and non-technical audiences.
• Experience in using Python and building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet.
• Fluency in written and spoken English.

Preferred Qualifications

• PhD degree in Computer Science or related technical, math, or scientific field.
• Proven knowledge of Generative AI and experience building applications with large foundation models.
• Proven knowledge of AWS platform and tools.
• Hands-on experience building ML solutions on AWS.
• High-impact thought leadership in AI/ML through blog posts, public presentations, or publications.

Amazon is an equal opportunities employer. We value diversity and encourage candidates with different experiences to apply. Your privacy and data security are top priorities. Please consult our Privacy Notice to learn about data collection and usage.

Amazon is committed to an inclusive workplace and does not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected statuses. For disability accommodations, please visit Hiring Accommodations.