Machine Learning Engineer, Level 4

Overview

Snap Inc (https : / / www.snap.com / en-US / ) 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 (https : / / www.snapchat.com / ), a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio (https : / / ar.snap.com / lens-studio), an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles (https : / / www.spectacles.com / ).

Snap Engineering (https : / / eng.snap.com / ) 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 (https : / / eng.snap.com / values) are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.

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 a relevant technical field such as computer science or equivalent years of practical work experience

3+ years of post-Bachelor’s machine learning experience; or Master’s degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field

Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other relevant applications of machine learning

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

Accommodations

If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information (https : / / docs.google.com / forms / d / e / 1FAIpQLScV7t31iR3yYR9ztGDHJpbvL63svWpb6s0afkBkLEjGnDx4Kg / viewform).

Policy

"Default Together" Policy at Snap : At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.

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.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).

Benefits

Our Benefits (http : / / careers.snap.com / benefits) : Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!

Compensation

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.

Zone A (CA, WA, NYC) :

The base salary range for this position is $173,000-$259,000 annually.

Zone B :

The base salary range for this position is $164,000-$246,000 annually.

Zone C :

The base salary range for this position is $147,000-$220,000 annually.

This position is eligible for equity in the form of RSUs.

Additional

A Decade of Snap : Learn about our origin story, values, mission, culture of innovation, and more.

CitizenSnap : In our third annual CitizenSnap Report, we demonstrate progress towards our environmental, social, and governance (ESG) goals, and we lay out our plans looking forward.

The DEI Innovation Summit : Watch highlights from the 2nd annual DEI Innovation Summit, which brings together thought leaders and DEI experts for a day of courageous conversations to enable bold action.

Snap News : Stay up to date on the latest and greatest product and innovation news at Snap

Applicant and Candidate Privacy Policy (https : / / storage.googleapis.com / hris-assets / Applicant_and_Candidate_Privacy_Policy.pdf)

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