Staff Machine Learning Engineer, Generative AI Modeling and Inference

Staff Machine Learning Engineer, Generative AI Modeling and Inference

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’s Generative ML Platform team builds cutting-edge AI technologies that power creative, scalable experiences for hundreds of millions of Snap chatters 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 Snap Inc!

What you’ll do:

Develop innovative machine learning technology and products that serve millions of Snap chatters

Build cutting-edge augmented reality experiences using generative models

Deliver generative machine learning experiences on device

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

Familiarity with Neural Networks and Deep Learning and Generative Modeling Deep understanding of mathematics and/or machine learning algorithms

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 technical field such as computer science, mathematics, statistics or equivalent years of experience

8+ years of post-Bachelor’s machine learning or related experience; or a Master’s degree in a technical field + 7+ years of post-grad ML or related experience; or a PhD in a related technical field + 4+ years of post-grad ML or related experience

Experience with Computer Vision or Generative Modeling techniques

Experience working with machine learning frameworks such as Tensor Flow, PyTorch, JAX, MLX, scikit-learn, or related frameworks

Preferred Qualifications:

Advanced degree in computer science or related field

Experience training large-scale diffusion models for images, videos or 3DKnowledge of distillation, quantization and model compression techniques

Knowledge of GPU, CPU, or NPU optimization techniques

Experience building and optimizing ML inference pipelines

Experience working with machine learning frameworks such as Tensor Flow, PyTorch, JAX, MLX, scikit-learn, or related frameworks

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,…