Staff Machine Learning Engineer, Generative AI Modeling, Inference

SNAP/SNAP

Staff ML Engineer developing generative AI, computer vision, and AR experiences for Snapchat. Building on-device inference and scalable machine learning products serving millions of users.

Posted 8/14/2026full-timeLos Angeles • California, New York, Washington • 🇺🇸 United StatesLead💰 $229,000 - $343,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in machine learning, particularly in generative modeling and deep learning, with a strong foundation in mathematics and algorithms. Proven ability to collaborate across teams and deliver innovative augmented reality experiences.

Highest-signal resume keywords

Machine Learning ExpertiseGenerative ModelingDeep LearningTensorFlowComputer Vision

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning AlgorithmsNeural NetworksGenerative Modeling TechniquesMathematicsLarge-Scale Diffusion ModelsModel Compression TechniquesML Inference PipelinesGPU OptimizationCPU OptimizationNPU Optimization

Soft Skills

Problem SolvingCollaborationIndependence

Tools & Technologies

TensorFlowPyTorchJAXMLXScikit-learn

Industry Keywords

Augmented RealityGenerative ModelsCross-Functional CollaborationResearch in Machine Learning

Tech Stack

Tools & technologies

PyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Develop innovative machine learning technology and products serving 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

Requirements

What you’ll need

Proven passion for machine learning and staying current with research
Familiarity with neural networks, deep learning, and generative modeling
Deep understanding of mathematics and/or machine learning algorithms
Ability to solve open, ambiguous problems
Ability to collaborate effectively with internal teams and external partners
Ability to work independently
Bachelor's degree in a technical field such as computer science, mathematics, or 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 plus 7+ years of post-graduate ML or related experience; or a PhD in a related technical field plus 4+ years of post-graduate ML or related experience
Experience with computer vision or generative modeling techniques
Experience with TensorFlow, PyTorch, JAX, MLX, scikit-learn, or related frameworks
Preferred: advanced degree in computer science or related field
Preferred: experience training large-scale diffusion models for images, videos, or 3D
Preferred: knowledge of distillation, quantization, and model compression techniques
Preferred: knowledge of GPU, CPU, or NPU optimization techniques
Preferred: experience building and optimizing ML inference pipelines

Benefits

Comp & perks

Paid parental leave
Comprehensive medical coverage
Emotional and mental health support programs
Compensation packages including equity in the form of RSUs
Equal opportunity employment