Skip to main content

Sr. Machine Learning Engineer, AFX - SalesNav

Job ID: 2666061 | Amazon Web Services, Inc.


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


Do you want work on inventing next generation software, in which generative AI is a driving building block? Are you an expert in development and use of ML, deep learning and looking to broaden that expertise by working with cutting edge concepts and tools? Do you have a passion for building end-to-end smart software products that deliver high business impact? AWS Field Experiences (AFX) team is looking for you!

The mission of AFX is to build software tools that make our field teams much more effective in winning opportunities and generating revenue for AWS. Our field teams are knowledge workers who operate on complex data such as collected intel about various AWS customers and their businesses, histories of our engagements with them, and documentation about the full range of AWS products and services. The tools and experiences we provide for the field teams put the right information to drive decision making and engagement with each customer. Our tools deliver this targeted intelligence through conversational interactions, suggestions, personalized recommendations, and high quality shareable generated content.

AFX is focusing on delivering those experiences with systems in which generative AI does multiple jobs, such as understanding and interpreting data, finding and accessing appropriate tools and resources, interfacing with the user, and generating content, and evaluating the quality of generated content. You will join our team of scientists and engineers that have already accrued skill and depth of knowledge in these areas, have had success building these applications, and are hungry to do more.

As a Machine Learning Engineer (MLE) you will contribute to the design, development and improvement of generative AI as well as traditional ML models and systems for various software products. In this role, you will be expected to:
- Invent software experiences and systems architectures that use Large Language Models (LLMs) and other forms of generative AI as building blocks.
- Work with Data Scientists, ML Engineers and product partners to design and deliver AI solutions into production at scale.
- Design and develop AI/ML models, workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our AI/ML models and systems.
- Deliver customer facing and/or underlying generative AI and ML solutions that empower AWS sellers to win in the marketplace of cloud software, services and solutions.

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.

We are open to hiring candidates to work out of one of the following locations:

Boston, MA, USA


- 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

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit