The Product Catalog is a strategic asset for Amazon. It powers unrivaled product discovery, informs customer buying decisions, offers a huge selection across a large number of categories and positions Amazon as the first stop for shopping online. Amazon Catalog Systems is looking for a customer-focused Software Development Engineer to help us make the world's best product catalog even better and improve the experience for millions of customers.
Amazon Catalog Systems leverages machine learning to find answers to the following questions from various unstructured data sources:
• Does this TV have built-in WiFi and which streaming services are supported?
• Can this wireless speaker play music from a flash drive?
• Is the "Pack of 4 with 6 bottles of 8 fluid ounce" at $50 baby bottled formula cheaper than the "3 packs of 36 ounces" for $110 powder version?
• Which cell-phone case is the most durable, ultra-thin and the best value for my money?
• Is this mat made of silicone and what are its dimensions?
• Where is this product manufactured?
• When searching for "apple case" do you mean a cell-phone case compatible with an iPhone or a crate of apples?
If you are excited about making the Amazon catalog more dynamic, smarter and changing the way we model and understand products and help customers discover, compare and purchase products, come join us! We are looking for people with initiative who enjoy diving deep into the data and coming up with innovative solutions. You will find challenges in:
Scalability: We process billions of records about products every day ranging from electronics to cosmetics. We build highly distributed systems and design algorithms that are able to handle these large amounts of data and operate with latencies in the tens of milliseconds. Where traditional solutions fail we develop approximate, distributed and streaming algorithms.
Ambiguity: We create, operationalize, monitor, and retrain thousands of ML models. Yes, you read it right - we are operating thousands of ML models simultaneously. We are always looking to raise the bar to manage the ML at scale. You can help us get there.
• Build scalable, efficient, and automated knowledge discovery systems
• Analyze and process large amounts of to extract valuable information from various sources (e.g. product catalog, search query ...)
• Actively participate in idea and roadmap generation.
• Work creatively through and around perceived limitations and/or challenges imposed by the delivery platform to enable delightful experiences for customers.
• Effectively present work to all levels of the leadership.
• Be an effective collaborator in a cross functional team of SDEs, Technical Program Managers, and Product Managers.
• 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.
• 2+ years of non-internship professional software development experience
• Bachelor's degree in Computer Science or a related field
• At least 3+ years of software development experience
• At least 1+ experience in a fast-paced and agile development environment to deliver high quality software against aggressive schedules
• Strong OO analysis, design, and development skills in Java and Scala
• Experience in Distributed Systems
• Strong verbal and written communication skills
• Advanced post graduate degrees (M.S., Ph.D.) in Computer Science or a related field
• Strong customer focus, ownership, urgency, and drive
• Experience building large-scale applications
• Expertise in delivering high quality, innovative applications.
• Optimizing current products to improve its performance and usability.
• Experience with AWS offerings or their equivalents (S3, EMR, Spark, DynamoDB, SWF)
• Experience in machine learning, data mining, artificial intelligence or statistics
• Excellent written and verbal communication.
Amazon is an Equal Opportunity-Affirmative Action Employer Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation