Highlights
You will be part of a team that uses technology including machine learning and graph modeling techniques, cloud computing services and highly available and scalable distributed systems that supports hundreds of millions of transactions across the globe. We provide highly effective, production ready relationship data insights (with transparency to audit, experiment, and enhance those insights) to allow teams across Amazon to make risk decisions.
Numbers & Facts
| Location | Tempe, AZ |
| Industry | Retail |
| Company Size | 10,000 employees or more |
| Year Founded | 1994 |
| Website | http://Amazon.com/militaryroles |
Description
Amazon's Risk Prevention organization constantly makes high judgment decisions across a wide breadth of constituents. We build and deliver services for Buyers, Sellers, Vendors and other customers. We ensure that Amazon is a safe and trustworthy place to shop and an amazing place to build a successful business selling products. We support our many partners in this journey. We face constant trade-offs and competing objectives that we need to appropriately balance. We have to do all of this at high scale which only happens through technology and science. You will be part of a team that uses technology including machine learning and graph modeling techniques, cloud computing services and highly available and scalable distributed systems that supports hundreds of millions of transactions across the globe. We are the Core Relations Engineering team in Risk and Fraud Detection organization. We provide highly effective, production ready relationship data insights (with transparency to audit, experiment, and enhance those insights) to allow teams across Amazon to make risk decisions. Our clients are the scientists, engineers, product managers, and investigators behind 45+ programs across Amazon. We provide all the necessary tools to engineer new features, explore graph-based insights, and detect risky relationships. Come join the best in class team of engineers, who are owners, and inventors. We are at the intersection of Machine Learning and Fraud Detection, while delivering customer impact at amazon scale. Interact with ML scientists on a daily basis, and build the services to beat to keep the bad guys out.
Key job responsibilities
Develop large scale, high performance, high reliability ML systems for data, feature, model and rule management. -
Work closely with ML scientists, understand the requirements, design and deliver innovative next-gen solutions to help preserve customer trust. Work as the owner of the system and operate excellent to provide stable and robust services to customers and other teams.
Innovate based on new ideas and build comprehensive system/features across the whole ML pipeline
About Company
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
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