Snap Inc

Machine Learning Engineer, Generative ML , Level 5

Snap Inc$209K — $313K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of machine learning experience post-Bachelor's; or a Master's with 4+ years; or a PhD with 1 year
  • Proficiency with Python or C++
  • Experience with PyTorch or TensorFlow
  • Strong understanding of mathematics and deep learning principles
  • Ability to work independently and collaboratively
  • Passion for staying updated on machine learning advancements
  • Desire to tackle open-ended problems

Responsibilities

  • Develop machine learning products for millions of Snapchat users
  • Create GenAI pipelines for diverse media types
  • Implement generative ML experiences directly on devices
  • Design advanced AR experiences using diffusion models
  • Collaborate on product prototypes with cross-functional teams

Benefits

  • Paid parental leave
  • Comprehensive medical coverage
  • Emotional and mental health support programs
  • Compensation packages that include long-term equity options
Full Job Description
Snap's Generative ML Platform team builds cutting-edge AI technologies that power creative, scalable experiences for hundreds of millions of Snapchatters worldwide. From multimodal LLMs and video generation to real-time AR, human understanding, and 3D content creation, we develop the full stack of generative AI, including foundational models, efficient infrastructure, and on-device and server-side inference. Our team creates intuitive tools, platforms, and agentic systems that empower creators, developers, and internal teams to bring ideas to life, while advancing personalized, human-centric experiences across mobile, web, and wearable devices like Spectacles.

We're looking for a Machine Learning Engineer to join our Generative ML team!

What you'll do:
  • Develop innovative machine learning technology and products that serve millions of Snapchatters
  • Work on state of the art GenAI pipelines for image, video, and audio generation
  • Deliver generative machine learning experiences on device
  • Build cutting-edge augmented reality experiences using generative and diffusion models
  • Partner with cross-functional Snap teams to explore and prototype new products


Knowledge, Skills & Abilities:
  • A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly
  • Strong software development skills in Python or C++
  • Proficiency working with major deep learning frameworks: PyTorch or TensorFlow
  • Knowledge of mathematics and deep learning foundations
  • Desire to solve open ambiguous problems
  • Desire to grow professionally, learn and help others
  • Ability to effectively collaborate with internal teams and external partners
  • Ability to work independently


Minimum Qualifications:
  • Bachelor's Degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience
  • 5+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 4+ year of post-grad machine learning experience; or PhD in a relevant technical field + 1 years of post-grad machine learning experience
  • Research or engineering experience in one or more of the following: generative models, efficient models, segmentation, object detection, classification, tracking, or other related applications of machine learning


Preferred Qualifications:
  • Master's degree or PhD in a related technical field
  • Experience developing real-time software for mobile applications
  • Knowledge of GenAI, especially image, video, and audio generation foundations
  • Knowledge of efficient model foundations
  • Track record of successful projects in GenAI field
  • Examples of your work such as open source projects, blog posts, Kaggle contests, top conference or journal publications, etc.


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.

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 $209,000-$313,000 annually.

Zone B:
The base salary range for this position is $199,000-$297,000 annually.

Zone C:
The base salary range for this position is $178,000-$266,000 annually.

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

About Snap Inc

Snap Inc. is a camera and social media company. It was founded in 2011 by Evan Spiegel, Bobby Murphy, and Reggie Brown. The company is known for its Snapchat app, which allows users to send photos and videos that disappear after being viewed. Snap Inc. is headquartered in Santa Monica, California and has offices around the world. The company went public in 2017 and is listed on the New York Stock Exchange.
Learn more about Snap Inc
Size
5,661 employees
Market Cap
$13.9 billion
Industry
Net Income
-$944.8 million
Founded
2016
5 Year Trend
+59.1%
Revenue
$2.5 billion
NASDAQ

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