The Prime Video Global App Experience organization operates at planet-wide scale and is a critical part of Prime Video’s flywheel.
Our client apps (mobile, living room, desktop, automotive) are the gateway to the Prime Video experience, enabling customers to quickly find something to watch at which point the app fades in the background and the customer is immersed in the storytelling.
We're reinventing how defects are detected in complex client apps, like Prime Video, and machine learning is going to be a key enabler to achieving that vision. The traditional approach of developing end-to-end integration tests on a per client basis isn't feasible at our global scale and large client distribution footprint. That approach to testing also doesn't detect "unknown/unknown" types of defects which occur more often than you'd expect when you operate a worldwide streaming video service used by hundreds of millions of customers.
If you are passionate about film, sport or TV and you’re looking for a role where you can maximize your impact as a world class Principal Applied Scientist then come help us achieve our mission of building the most customer-centric, immersive and visually-rich video streaming experience on any device.
Key job responsibilities
As a Principal Applied Scientist in the Prime Video Global App Experience organization you will leverage your deep subject matter expertise in applied machine learning to prototype and productionalize approaches to detect defects in our client apps.
The space is ambiguous. No one is going to tell you which types of defects to work on nor which ML techniques to apply (classical ML, Deep Learning, CVML, NLP, etc) . Your role is to assess the opportunities, tailwinds, headwinds and risks. Then develop a vision and execute on a plan to achieve meaningful outcomes for our customers. At our scale improving CX metrics by just a few basis points can result in the reduction of millions of defects experienced by our customers annually.
You will also work with external academic partners to support our in-house talent with direct access to cutting edge research and mentoring.
