Machine Learning Engineer, AWS Applied AI Solution

Amazon.com Inc

Seattle, WA

JOB DETAILS
SKILLS
Amazon Web Services (AWS), Artificial Intelligence (AI), Best Practices, Business Solutions, Code Reviews, Cross-Functional, Customer Experience, Customer Relations, Data Analysis, Knowledge Transfer, Leadership, Machine Learning, Mentoring, Model Validation, Production Systems, Systems Scalability, Team Building, Team Player
LOCATION
Seattle, WA
POSTED
30+ days ago

As part of the AWS Applied AI Solutions organization, our vision is to provide business applications, leveraging Amazon"s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We accelerate our customers" businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. Our team combines Amazon"s real-world experience with state-of-the art AI to create opinionated, turnkey solutions that are no-brainers to buy and easy to use.

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 system, 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 Company

A

Amazon.com Inc

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
COMPANY SIZE
10,000 employees or more
INDUSTRY
Retail
FOUNDED
1994
WEBSITE
http://Amazon.com/militaryroles