ML Engineering Manager - Ad Experience & Moderation

Snap Inc.; Los Angeles (CA); On-site; USD 229,000 - 343,000; Full time

Benefits offered by this job

RSUs

Job summary

Snap Inc. is seeking a Manager, Machine Learning Engineering for the Advertiser Experience ML team in California. You will lead engineers building models, data pipelines, and ad‑related ML systems powering review, fraud detection, and recommendations.

You will set the technical strategy, drive roadmaps, and scale LLM‑powered workflows while ensuring quality, privacy, and cost control. Strong cross‑functional collaboration and leadership are essential.

Qualifications

• Bachelor’s in CS or related technical field.
• 8+ years post‑Bachelor’s ML industry experience.
• 1+ years of experience leading machine learning engineering teams.

Responsibilities

• Lead a team of ML engineers and software engineers building models, data pipelines, and production-grade systems.
• Set the team's technical strategy and roadmap; prioritize across product and platform needs.
• Scale LLM-powered ad review and agentic systems while preserving precision and policy quality.
• Partner with Product, Data Science, Business Integrity, Ranking, Attribution, and Recommendations teams to define success metrics and deliver outcomes.
• Maintain deep technical involvement from design to hands‑on contributions when needed.
• Hire, develop, and retain a high‑performing team with focus on model quality, reliability, cost, privacy, and responsible AI.

Skills

Team leadership

Production ML systems

LLM deployment

Cross‑functional collaboration

Cost & latency awareness

Education

Bachelor's in CS or related field

Tools

PyTorch

TensorFlow

Distributed systems

Job description

Snap Inc. is seeking a Manager, Machine Learning Engineering for the Advertiser Experience ML team in California. You will lead engineers building models, data pipelines, and ad‑related ML systems powering review, fraud detection, and recommendations.

You will set the technical strategy, drive roadmaps, and scale LLM‑powered workflows while ensuring quality, privacy, and cost control. Strong cross‑functional collaboration and leadership are essential.