Job Description

Job ID: 2855378 | Amazon.com Services LLC

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.

BASIC QUALIFICATIONS

1. 10+ years of tech industry or equivalent experience
2. Experience working effectively with science, data processing, and software engineering teams
3. Graduate degree in Computer science/Math or related field.
4. Experience in building complex, real-time systems involving AI, ML, NLP with successful delivery to customers.
5. Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements. Ability to take a project from requirements gathering and design to actual product launch
6. Computer Science fundamentals in data structures, algorithm design and complexity analysis.
7. Ability to develop a machine learning strategy for non-traditional areas such as developer productivity, software quality assurance (testing), availability, app performance/fluidity and latency reduction.
8. Exceptional customer relationship skills including the ability to discover the true requirements underlying feature requests, recommend alternative technical and business approaches, and lead science efforts to meet aggressive timelines with optimal solutions.
9. Demonstrated track record of peer-reviewed scientific publications that advance state-of-the art for applied science.

PREFERRED QUALIFICATIONS

1. PhD degree in Computer Science or related field.
2. Demonstrated ability to push the envelope in at least one machine learning domain (e.g. deep learning, NLP, reinforcement learning)
3. Expertise in large language models or demonstrated ability to develop this expertise quickly.
4. Experience in Computer Science fundamentals such as object-oriented design, algorithm design, data structures, problem solving, and complexity analysis.
5. Work with academic partners to support our in-house talent with direct access to cutting edge research and mentoring.
6. More than 15+ years of business/academic experience in building machine learning models.
7. Excellent written and verbal technical communication with an ability to present complex technical information in a clear and concise manner to a variety of audience.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit this link for more information.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit this link .

Posted: January 9, 2025 (Updated 33 minutes ago)

#J-18808-Ljbffr

Job Tags

Full time, Worldwide,

Similar Jobs