Snap Inc
is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company's three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.
About Snap Engineering
Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We're deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.
Position Overview
We're looking for a Machine Learning Engineer to join Snap Inc!
What you'll do:
Create models which help drive value for users, advertisers, and our company Evaluate the technical tradeoffs of every decision Perform code reviews and ensure exceptional code quality Build robust, lasting, and scalable products Iterate quickly without compromising quality Knowledge, Skills & Abilities:
Strong understanding of machine learning approaches and algorithms Able to prioritize duties and work well on your own Ability to work with both internal and external partners Skilled at solving open ambiguous problems Strong collaboration and mentorship skills Minimum Qualifications:
Bachelor's degree in technical field such as computer science, mathematics, statistics or equivalent years of experience 5+ years of experience in industry developing machine learning models for ranking, recommendations, search, content understanding, or image generation Preferred Qualifications:
Advanced degree in computer science or related field Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks Experience working with machine learning, ranking infrastructures, and system design #J-18808-Ljbffr