Staff Machine Learning Engineer, Diffusion, Generative Modeling and Inference

About the role

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.

Responsibilities

• 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

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

Skills

• 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

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

Pay

In the United States, work locations are assigned a pay zone which determines the salary range for the position. Zone A (CA, WA, NYC): $229,000-$343,000 annually. Zone B: $218,000-$326,000 annually. Zone C: $195,000-$292,000 annually. This position is eligible for equity in the form of RSUs.

Schedule

Snap practices a "default together" approach and expects team members to work in an office 4+ days per week.

Benefits

• Paid parental leave
• Comprehensive medical coverage
• Emotional and mental health support programs
• Compensation packages that let you share in Snap's long-term success