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Snap Inc.

Machine Learning Engineer, Level 3

Posted 53 Minutes Ago
Be an Early Applicant
Hybrid
New York, NY, USA
100K-176K Annually
Junior
Hybrid
New York, NY, USA
100K-176K Annually
Junior
Design, train, evaluate, and deploy machine learning models for core Snapchat products. Perform data analysis, model training, and production deployment. Collaborate with cross-functional partners to implement ML-driven features, use AI tools and scalable engineering workflows, and maintain high standards for code correctness, security, and production readiness.
The summary above was generated by AI

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 operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.


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.

We’re looking for a Machine Learning Engineer to join Snap Inc!

What you’ll do:

  • Build and deploy machine learning models for core Snapchat products

  • Apply established ML techniques to solve well-defined, real-world problems

  • Contribute to the ML lifecycle, including data analysis, model training, evaluation, and production deployment

  • Collaborate with cross-functional partners and teammates to implement and launch ML-driven features

  • Utilize AI tools and high velocity engineering workflows to design and ship scalable services while upholding rigorous standards for code correctness, security, and production ready quality code

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

  • Adaptability in learning and applying evolving AI systems and tools to remain at the forefront of engineering trends and modern development practices

Minimum Qualifications:

  • Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience

  • 1+ years of post-Bachelor’s machine learning experience; or Master’s degree 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

If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.

"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).

Our 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 $118,000-$176,000 annually.


 

Zone B:

The base salary range for this position is $112,000-$167,000 annually.

Zone C:

The base salary range for this position is $100,000-$150,000 annually.

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

Snap Inc. New York, New York, USA Office

Snap NYC is in the heart of Times Square in the former New York Times office building!

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