Take the earth's most customer-centric company. Mix in millions of
shoppers spending billions of dollars annually and an opportunity to use
your skills in machine learning and data mining to improve product
recommendations and search. What do you get? The best job in the
internet today - PERIOD.
The charter of Amazon’s Personalization team is to recommend the “right" product to the “right" customer at the “right" time. We generate
personalized product recommendations for millions of customers each day, in a blink of an eye, thousands of times a second.
If you are a strong software engineer with a background in Machine
Learning, who is passionate about turning massive amounts of data into
actionable insights, then this is the right opportunity for you.
You will work with a team of highly skilled and motivated scientists and
engineers, who are building the next generation of personalization
products at Amazon. Our team advances the state-of-the-art in
personalization by using machine learning, and leveraging Amazon’s vast computing resources (AWS) and data. As part of your job, you will deal with large amounts of training data, rapidly prototype new models that meet stringent performance requirements, and perform offline and online testing.
- Research and use of statistical techniques to create scalable
solutions for business problems
- Analyze and extract relevant information from large amounts of
Amazon's historical business data to help automate and optimize key
features and processes
- Work closely with scientists and engineering teams to create and
deploy new features
- Work closely with stakeholders to optimize various business operations
- Establish scalable, efficient, automated processes for large scale
data analyses, model development, validation and implementation.
- Track general business activity and provide clear, compelling
management reporting on a regular basis
By submitting your application here, you can apply once to be considered for multiple Software Engineering openings across various Amazon teams. If you are successful in passing through the initial application review and assessment, you will be asked to submit your career and personal preferences so that our dedicated recruiters can match you to the right role based on these preferences.
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
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· 2+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· 3+ years of experience in software development. Experience building large platform systems.
· Jack of many development languages: C++, Java, Python, master in some.
· Experience with full development life cycle for large-scale software products including extensive experience with service oriented architectures, design patterns, web services, and web applications/services development.
· A PhD in CS, Machine Learning or in a highly quantitative field.
· Prior work experience as an applied scientist or a data scientist at a consumer product company.
· 5+ years of practical experience applying ML to solve complex problems in an applied environment
· Experience using an object-oriented language to write production-ready code.
· Strong record of publications in one of the following areas: information retrieval, natural language processing, recommender systems, reinforcement learning, multi-armed bandits.
· Industry experience working with search engines, autocomplete, or recommender systems.