Applied Scientist, Machine Learning Accelerator

Develop an understanding for a custom machine learning instruction set architecture.

Model correctness of instruction streams using first order logic.

Create custom API”s to allow control over scheduling and randomness.

Deploy algorithms to ensure concurrent code is safely constructed.

Create coverage metrics to ensure solution space coverage.

Use novel methods like machine learning to automate content creation.

About the team

Utility Computing (UC)

AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services.

Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.

Algorithms, Amazon Elastic Compute Cloud (EC2), Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Application Programming Interface (API), Cloud Computing, Content Development, Customer Support/Service, Database Administration, Design Verification, Hardware Architecture Design, Intellectual Property (IP), Internet of Things, Legal, Machine Learning, Metrics, Problem Solving Skills, Product/Service Launch, Regulatory Requirements, Requirements Validation/Verification, Software Design, Surface Mount Technology, Technical/Engineering Design, Test Plan/Schedule, Utility Computing, Verification Engineering

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