ML Engineering Manager - LLM, Ads & Platform

SNAP, Inc.; Los Angeles (CA); Sur place; USD 229 000 - 343 000; Plein temps

Avantages offerts par ce poste

Equity (RSUs)

Paid parental leave

Comprehensive medical coverage

Mental health support

Résumé du poste

Snap Inc. is seeking an experienced Machine Learning Engineering Manager to join the Advertiser Experience ML team.

You will lead ML engineers and software engineers to build models, data pipelines, and agentic systems powering ad review, fraud detection, advertiser understanding, and recommendations. The role requires deep ML knowledge, experience with production systems, and a track record of delivering measurable business outcomes.

Qualifications

• Bachelor's in a related technical field or equivalent years of experience.
• 8+ years of post-Bachelor’s ML industry experience; or a Master’s degree + 7+ years ML experience; or a PhD + 4+ years ML experience.
• 1+ years of experience leading machine learning engineering teams.

Responsabilités

• Lead a team of ML and software engineers building models, agentic systems, and data pipelines for ad review, fraud detection, and advertiser understanding.
• Set the team’s technical strategy and roadmap; prioritize across product and platform teams.
• Scale LLM-powered ad review while maintaining precision and policy quality.
• Partner with Product, Data Science, Business Integrity, Ranking, Attribution, and Recommendations teams to define success metrics and align roadmaps.
• Maintain hands-on involvement and ensure high model quality, reliability, and privacy.

Connaissances

Machine learning

LLM/policy & AI

Leadership

Cross-functional collaboration

Privacy & responsible AI

Formation

Bachelor's in a related technical field (CS/CE/ML)

Master's + 7+ years ML experience

PhD + 4+ years ML experience

Outils

PyTorch

TensorFlow

Description du poste

Snap Inc. is seeking an experienced Machine Learning Engineering Manager to join the Advertiser Experience ML team.

You will lead ML engineers and software engineers to build models, data pipelines, and agentic systems powering ad review, fraud detection, advertiser understanding, and recommendations. The role requires deep ML knowledge, experience with production systems, and a track record of delivering measurable business outcomes.