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# Machine Learning Engineer, Generative ML, Level 4

- **Company:** Snap Inc.
- **Location:** Palo Alto, CA, United States
- **Experience:** Experienced
- **Salary:** $173,000.0 - $259,000.0
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), Mobile Application Software, Python (Programming Language), Machine Learning, Language Modeling, Real-Time Operating Systems, Tensorflow, Software Engineering, Pytorch, Deep Learning, Kaggle, Generative AI, Information Technology, Free and Open-Source Software
- **Published:** October 26, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3467519378&tx=UT5652TYD&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* A proven passion for machine learning; you stay up-to-date with research and are excited about prototyping new ideas quickly
 * Strong software development skills in Python or C++ Proficiency working with major deep learning frameworks: PyTorch or TensorFlow
 * Knowledge of mathematics and deep learning foundations
 * 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, * Bachelor's Degree in a technical field such as computer science, mathematics, statistics or equivalent years of experience
 * 3+ years of post-Bachelor's machine learning experience; or Master's degree in a technical field + 2+ year of post-grad machine learning experience; or PhD in a relevant technical field
 * Research or engineering experience in one or more of the following: generative models, efficient models, diffusion models, language models, or other related applications of machine learning, * Master's degree or PhD in a related technical field
 * Experience developing real-time software for mobile applications
 * Knowledge of GenAI, especially image, video, language and audio generation foundations
 * Knowledge of efficient model foundations
 * Track record of successful projects in GenAI field
 * Examples of your work such as open source projects, blog posts, Kaggle contests, top conference or journal publications, etc.