Principal Machine Learning Engineer, Platform Integrity Engineering, Level 7

Posted Yesterday
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6 Locations
Hybrid
235K-414K Annually
Expert/Leader
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Snap is a technology company.
The Role
Designs, scales, and leads machine learning systems that detect harmful content and bad actors, support content moderation, and promote platform integrity. Provides technical direction across the ML organization, partners with cross-functional leadership, improves ML infrastructure and operational excellence, and delivers performant, scalable models using modern deep learning techniques.
Summary Generated by Built In

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 Principal Machine Learning Engineer to join the Platform Integrity Engineering team at Snap!


What you’ll do:


  • Design, implement, and scale critical machine learning models and systems to protect Snapchatters around global from harmful content and bad actors, promote a healthy content ecosystem through effective moderation, and ensure regulatory compliance
  • Collaborate with cross-functional teams to set and align on machine learning strategies to meet company objectives
  • Stay up-to-date with the latest technology in machine learning and apply this knowledge to tackle complex problems in innovative ways
  • Collaborate with leadership to up-level the ML tech stack and improve the performance of the organization
  • Work across teams to understand product requirements, evaluate trade-offs, and deliver the solutions needed to build innovative products or services
  • Advocate for and apply best practices when it comes to availability, scalability, operational excellence, and cost management
  • Provide technical direction that influences the entire ML community

Knowledge, Skills & Abilities:


  • Strong understanding of machine learning, deep learning, computer vision, natural language processing, and LLMs/VLMs approaches and algorithms, and their applications to Trust and Safety, Content Moderation, and Content Quality domains
  • Experience setting the direction for a team whose primary output is online machine learning models to proactively detect harmful content and bad actors, moderate content supply to promote healthy content ecosystem, and automate moderation tasks with high precision
  • Ability to design, train, and optimize advanced machine learning models
  • Excellent programming and software design skills
  • Ability to proactively learn new concepts and technology and apply them at work
  • Skilled at solving ambiguous problems and leading and executing complex technical initiatives
  • Strong collaboration and mentorship skills

Minimum Qualifications:


  • Bachelor's in a technical field such as computer science, mathematics, statistics or equivalent years of experience
  • 9+ years of post-Bachelor’s machine learning experience; or a Master’s degree in a technical field + 8+ year of post-grad ML experience; or a PhD in a related technical field + 5+ years of post-grad ML experience
  • 2+ years of experience with technical leadership or acting as the domain-expert to a technical organization
  • Experience developing and shipping performant and scalable machine learning models 
  • Experience with TensorFlow, PyTorch, or related deep learning frameworks

Preferred Qualifications:


  • Experience in online safety and integrity, including Trust and Safety, Content Moderation, and Content Quality
  • Experience in developing multimodal models and LLMs/VLMs in harmful content detection, and utilizing the state-of-the-art machine learning techniques to detect bad actors with features such as social, time sequence, and user behavioral signals
  • Advanced degree in a related field such as machine learning, computer vision, natural language processing, or mathematics
  • Experience partnering with cross-functional executives and management across a globally distributed organization and exercising sound judgment
  • Track record of delivery in rapidly changing, highly collaborative, multi-site, multi-stakeholder environments
  • Experience working with a diverse group of engineers
  • Experience contributing to AI publications

"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 $276,000-$414,000 annually.


 

Zone B:

The base salary range for this position is $262,000-$393,000 annually.

Zone C:

The base salary range for this position is $235,000-$352,000 annually.

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

If you believe this job description is missing required pay transparency information, please submit a report through this form: Job Description Pay Range Disclosure.

Skills Required

  • Bachelor's degree in computer science, mathematics, statistics, or another technical field, or equivalent experience
  • 9+ years of post-Bachelor's machine learning experience; or a Master's degree with 8+ years of post-graduate ML experience; or a PhD with 5+ years of post-graduate ML experience
  • 2+ years of technical leadership experience or experience serving as a domain expert for a technical organization
  • Experience developing and shipping performant and scalable machine learning models
  • Experience with TensorFlow, PyTorch, or related deep learning frameworks
  • Experience in online safety and integrity, including Trust and Safety, Content Moderation, or Content Quality
  • Experience developing multimodal models and LLMs/VLMs for harmful content detection
  • Advanced degree in machine learning, computer vision, natural language processing, mathematics, or a related field
  • Experience partnering with cross-functional executives and management in a globally distributed organization
  • Experience delivering in rapidly changing, collaborative, multi-site, multi-stakeholder environments
  • Experience working with diverse groups of engineers
  • Experience contributing to AI publications

What the Team is Saying

Xiaolin
Yvette
Matt
Jasmeet
Xueyin (Sherry)
Amir
Jung
Xu
Talia Mason
Maureen Ufomadu
Vincent Pagnard-Jourdan
Pulkit Trivedi

Snap Inc. Compensation & Benefits Highlights

  • Healthcare Strength — Health coverage includes multiple medical plan options (PPO/HDHP/HMO), dental and vision, HSA/FSA, mental-health support (e.g., Lyra), and wellness programs. Family-building benefits and services like One Medical are also part of the package.
  • Parental & Family Support — Parental leave is described as generous—up to 26–28 weeks for birthing parents and up to 16 weeks for non-birthing parents—alongside adoption, surrogacy, fertility preservation, backup childcare, caregiver assistance, and return-to-work support.
  • Retirement Support — A 401(k) with company match (immediate vesting cited), plus pre-tax, Roth, and after-tax contributions including a Mega Backdoor Roth option, supports long-term savings. Additional financial wellness tools complement the retirement program.

Snap Inc. Insights

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The Company
HQ: Santa Monica, CA
5,000 Employees
Year Founded: 2011

What We Do

We contribute to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.

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Snap Inc. Teams

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Product + Tech
Team
Machine Learning
Team
Sales
About our Teams

Snap Inc. Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Our “default together” approach is an 80/20 model where we are asking team members to spend 80% of the time, on average, in the office, with the remaining 20% of the time spent remote.

Typical time on-site: 4 days a week
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