Sr. Machine Learning Engineer, AWS Applied AI Solution

About the role

AWS Applied AI Solutions (AAIS) is building toward a future where every business innovates with Amazon AI teammates. To get there, we build AI solutions that improve human capabilities and transform entire business functions. We create end-to-end products that surprise and delight out-of-the-box, making complex things easy and hard things possible, with no cloud experience required. We start with customers who embrace the future and build bridges to meet the rest where they are. We pursue ambitious opportunities with conviction, and we are looking for builders who share that mindset.

We're building applied AI solutions that businesses love and trust. Our ambition is to become the partner companies rely on to run their business every day - putting AI to work to deliver better customer experiences, operational excellence, and faster innovation. We're a fast-moving scrappy team building a new agentic product from the ground up. If bias for action is your favorite leadership principle you'll fit right in.

The Role: We're seeking a talented Senior Machine Learning Engineer with expertise in agentic systems, production ML systems, and scalable deployment architectures. You'll bridge the gap between state-of-art research and customer-facing products, contribute to our collaborative and innovative culture, and deliver production-ready ML solutions that raise the bar for the entire team.

What You'll Do • Work closely with Applied Scientists and cross-functional engineering teams to transform research code into robust scalable production systems • Own end-to-end deployment at scale of Generative AI and ML methods ensuring reliability and performance • Establish scalable, efficient, automated processes for large-scale data analysis, machine learning model development, model validation, and serving • Research and implement innovative approaches for efficient model deployment training and optimization • Document processes and methods for both technical and non-technical audiences ensuring knowledge transfer and best practices • Contribute to code reviews and maintain high engineering standards across the team • Mentor junior MLEs and actively participate in recruiting top talent to grow the team • Present outcomes and explain technical approaches to senior leadership translating complex concepts into business impact

About the team

Amazon 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.

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.

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.