Full Job Description
Snapchat is a camera and messaging app that connects people to their friends and the world. Every day around the globe, millions of people use Snapchat to communicate with friends, build relationships, play, and learn. No matter where you are or how you express yourself, it’s always the fastest way to share a moment!
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.
Some core features we build and maintain include Snapchat’s Camera, Creative Tools, Maps, Chat, Memories, Stories, Discover, Games, and Minis. Our Infrastructure teams deliver an innovative and cost-efficient platform that ensures Snapchat is the fastest way to communicate with your friends, no matter where you are in the world. We have one of the fastest growing digital ad platforms, and our Monetization teams drive measurable returns for advertisers through novel ad formats like Augmented Reality. As a Snap Engineering team member, you’ll help us build the future of communication.
We're looking for an Engineering Manager, Machine Learning to join the Ad Ranking Engineering team. Working from our Seattle, WA office, you will be tasked with leading the development of new advertising products that help our partners achieve their business goals on the Snap platform.
What you’ll do:
Lead machine learning engineers to create models which drive value for our users, advertising partners, and our company
Design and implement new advertising products end-to-end helping advertisers achieve their business goals
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 and their application to advertising domain
Experience setting the direction for a team whose primary output is online ranking/recommendation models
Excellent verbal and written communication skills, with high attention to detail
Experience collaborating with internal and external stakeholders at all levels of a company
Experience in solving open ambiguous problems from end to end
Possesses a desire to learn and help others
BS/BA degree in technical field such as Computer Science, Mathematics, Statistics or equivalent years of experience
8+ years ML industry experience or 7+ years ML industry experience and PhD in a related field
Experience leading ML teams that focus on online ranking/recommendations
M.S. degree and/or PhD 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 distributed systems
Experience working with machine learning, ranking infrastructures, and system designs
Ability to proactively learn new concepts and apply them at work
Experience in online advertising domain
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. If you have a disability or special need that requires accommodation, please don’t be shy and contact us at firstname.lastname@example.org .