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's three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.

We're looking for Machine Learning Engineers to join the Generative ML Platform team at Snap Inc!

What you'll do:

1. Develop ML-tools and ML-products that serve millions of Snapchatters on a daily basis
2. Build cutting-edge augmented reality experiences with diffusion/flow matching models and GANs
3. Deliver GenAI experiences for the edge devices
4. Work on state of the art GenAI pipelines for image and video generation
5. Work closely with other Snap teams to introduce, prototype and launch new products

Knowledge, Skills & Abilities:

1. A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly
2. Knowledge of mathematics and deep learning foundations
3. Ability to effectively collaborate with internal teams and external partners
4. Ability to work independently

Minimum Qualifications:

1. Bachelor's Degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience
2. Proven research or engineering experience in one or more of the following: neural rendering, generative models, segmentation, object detection, classification, tracking, or other related applications of deep learning
3. Experience with the major deep learning frameworks: PyTorch or TensorFlow
4. Strong programming skills in Python or C++

Preferred Qualifications:

1. Experience developing real-time software for mobile applications
2. Knowledge of computer graphics foundations
3. Track record of successful projects in GenAI field
4. Examples of your work such as open source projects, blog posts, Kaggle contests, top conference or journal publications, etc.

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