Machine Learning Engineer II - Ads

Toronto, Ontario, CAN

Full Time
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Posted 4 weeks ago

Amazon is investing heavily in building a world-class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising solutions that drive discovery and sales. Our Sponsored Products helps merchants, retail vendors, and brand owners succeed via native advertising that grows incremental sales of their products sold through Amazon. We optimize systems and ad placements to match advertiser’s demand with publisher’s supply using a combination of machine learning (ML), deep learning and multi-objective constrained optimization, as well as ultra-low latency and high-volume engineering systems. Our goals are to help buyers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and to build a major, sustainable business that helps Amazon continuously innovate on behalf of all customers. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.

The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team.

As a Machine Learning Engineer, you will drive the direction of our technical solutions, and work on many different technologies such as deep learning, AWS, Auto ML, realtime ML serving systems. You will design, code, troubleshoot, and support scalable offline machine-learning pipelines and online serving components. You will work closely with applied scientists to optimize the performance of machine-learning models, improve team’s machine learning productivity, and advance the technical foundation to empower our science innovation. What you create is also what you own.

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.
· Bachelor's degree in Computer Science or related disciplines

Preferred Qualifications

· Experience in building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search, etc.
· Experience with Big Data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza
· Strong proficiency with Java, Python, Scala or C++
· Coursework or thesis in machine learning, data mining, information retrieval, statistics or natural language processing
· Advanced knowledge of performance, scalability, enterprise system architecture, and engineering best practices
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation/Age.

Job tags: AWS Big Data Data Mining Deep Learning Engineering Hadoop Java Machine Learning ML Python Scala Spark