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 Snap Inc!

What you'll do:

• Develop innovative machine learning technology and products that serve millions of Snapchatters
• 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 TensorFlow, 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 3D
• Knowledge 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 TensorFlow, PyTorch, JAX, MLX, scikit-learn, or related frameworks

"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 $229,000-$343,000 annually.

Zone B:
The base salary range for this position is $218,000-$326,000 annually.

Zone C:
The base salary range for this position is $195,000-$292,000 annually.

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