SDE-Machine Learning

Seattle, Washington, USA

Applications have closed

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Just finished “The Boys” and “Coming 2 America” and want to watch more of the same? Looking for a movie that's like The Big Sick? So are millions of our Prime Video customers. The Prime Video Relevance team suggests videos that are relevant and tailored to our customers’ schedules and environments. We help our customers find content they didn’t even known they were looking for, continuing to surprise them with the depth of our catalog

A day in the life
Some examples of the things we work on:
· Using Neural Networks/Deep Learning techniques to find titles that customers will enjoy
· Build and operate services/system that deliver millions of recommendations per second
· Extend models and algorithms to support our ever growing ways of consuming content (subscriptions, live, rentals etc), dealing with unique challenges such as observational bias and rapidly scaling dimensions
· Constantly experimenting with changes to the underlying algorithms and models to deliver relevant content to a wide variety of customer experiences with impact on a product that is used by millions of people around the world.

About the hiring group
Our team is already either exploring or leveraging: residual networks for surfacing more of our catalog, auto encoders and clustering to identify niche content carousels, attention networks to better understand what customers are currently into, reinforcement learning to optimize for the long term, graph convolution networks to understand the complex interaction of our customers with the videos they enjoy (or don’t), and transfer learning to optimize to different customer objectives. Not only will you be exposed to the cutting edge of machine learning research, you'll collaborate with a talented team of engineers and scientists to create services to run these predictions on distributed systems at incredible scale and speed. As a member of the Prime Video Relevance team, you will spend your time as a hands-on engineer and a technical leader. You will play a key role in building and guiding software products and features from the ground up. You will use a wide range of technologies, programming languages and systems. Your responsibilities will include all aspects of software development. At the end of the day, you will have the reward of seeing your contributions delight Prime Video customers worldwide.

Job responsibilities
· Being the lead engineer on a team, mentoring junior engineers, ensuring the right development practices are followed.
· Being very hands-on; working with an engineering team to manage the day-to-day development activities by leading architecture decisions, participating in design reviews, code reviews, and implementation.
· Maintaining current technical knowledge to support a rapidly changing technology stack, always being on the look out for new technologies and working with management and development teams in exploring new technologies.
· Communicating with users, other technical teams, and senior management to collect requirements, describe software product features, technical designs, and product strategy.


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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Basic Qualifications


· 2+ years of non-internship professional software development experience
· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
· 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.


Preferred Qualifications

· Master’s degree or PhD in Computer Science or equivalent
· Experience with critical, 24x7 systems
· Experience building complex software systems that have been successfully delivered to customers
· Experience building large scale distributed services
· Experience building and deploying machine learning models
· Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
· Experience designing and deploying Big Data pipelines with tools such as Hadoop, Spark or MapReduce.
· Strong system design and architecture experience.

Tags: Big Data Computer Science Data pipelines Deep Learning Distributed Systems Engineering Hadoop Machine Learning ML models PhD Pipelines Research Spark Testing

Perks/benefits: Team events

Region: North America
Country: United States
Job stats:  27  3  0

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