Senior ML Engineer for Large-Scale Production Systems

SNAP, Inc.; Los Angeles (CA); On-site; USD 173,000 - 259,000; Full time

Benefits offered by this job

RSUs eligible

Job summary

Snap Inc. is seeking a Machine Learning Engineer to build and deploy models powering Snapchat’s core experiences. You will own the ML lifecycle from data analysis to production deployment and partner with cross-functional teams to prototype ML-driven features that scale to millions of users.

You will leverage modern ML techniques, ensure rigorous code quality and security, and mentor teammates while adapting to evolving AI tools and systems in a fast-paced engineering environment.

Qualifications

• Bachelor's degree in a technical field; strong ML foundation required.
• 3+ years of post-bachelor ML experience or advanced degree with ML focus.
• Experience with ranking, recommendations, search, or content understanding is preferred.

Responsibilities

• Build and deploy ML models powering core products serving millions.
• Apply modern ML techniques to large-scale real-world problems.
• Own end-to-end ML lifecycle from data analysis to production deployment.
• Collaborate with cross-functional teams to prototype and launch ML-driven features.
• Ensure code correctness, security, and production-ready quality.

Skills

ML fundamentals

Ranking & recommendations

Production ML pipelines

Cross-functional collaboration

Ambiguity handling

Mentorship

AI tooling literacy

Education

Bachelor's degree in CS or related

3+ years ML experience

Master's or PhD preferred

Tools

TensorFlow

PyTorch

scikit-learn

Spark ML

Job description

Snap Inc. is seeking a Machine Learning Engineer to build and deploy models powering Snapchat’s core experiences. You will own the ML lifecycle from data analysis to production deployment and partner with cross-functional teams to prototype ML-driven features that scale to millions of users.

You will leverage modern ML techniques, ensure rigorous code quality and security, and mentor teammates while adapting to evolving AI tools and systems in a fast-paced engineering environment.