Sr. Machine Learning Engineer, AFX - GenAI

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

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AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

Senior Machine Learning Engineer, Gen AI AWS Field Experiences


DESCRIPTION
Senior Machine Learning Engineer - AWS Field Experiences (AFX)

Are you passionate about inventing next-generation software powered by generative AI? Do you want to expand your expertise in ML and deep learning while working with cutting-edge concepts and tools? Do you have a passion for building end-to-end the smart software products that can deliver high business impact? AWS Field Experiences (AFX) team is looking for you!

As a Senior Machine Learning Engineer at AFX, you will be at the forefront of building AI-driven software tools that empower our field teams to win opportunities and generate revenue for AWS. You will work with a team of passionate scientists and engineers to design, develop, and improve generative AI and traditional ML models that drive multiple software products.

Key responsibilities:

* Innovate system architectures that use Large Language Models (LLMs) and other forms of generative AI as building blocks
* Leverage diverse data sources to maximize business impact through ML and AI methods
* Design and develop end-to-end, robust, and scalable pipelines for data preparation, model training, deployment, and monitoring
* Collaborate with scientists, engineers, and product partners to deliver intelligent, feature-rich software product
* Mentor and educate our colleagues and customers about how AI technology works, and the ways it may change how knowledge work is done.

About the team
About the team
About AWS
Diverse Experiences
AWS 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 the most successful 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 (gender diversity) 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. 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.

Work/Life Balance
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.

About Sales, Marketing and Global Services (SMGS)

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.