Machine Learning Engineering Manager (Advertiser Experience ML)

Join Snap as a Machine Learning Engineering Manager for the Advertiser Experience ML team. In this role, you will lead a team of machine learning engineers and software engineers, set the team's technical strategy, and maintain deep technical involvement in the team's work. You will also partner with various teams to define success metrics and deliver measurable outcomes. The position offers a comprehensive benefits package, including generous time off, medical coverage, and a 401(k) plan.

Lead a team of machine learning engineers and software engineers to build models, agentic systems, and data pipelines for ad review, fraud detection, and advertiser recommendations.

Responsibilities

• Set the team's technical strategy and own its roadmap, making prioritization calls across product and platform teams.
• Scale LLM-powered and agentic ad review to automate moderation decisions without lowering precision or policy quality.
• Track record of setting a team strategy and turning it into a roadmap that delivered business results
• Technical depth to guide design decisions across modeling, data pipelines, and inference
• Experience building production systems with large language models, including evaluation, iteration, and managing cost and latency
• Deep understanding of machine learning approaches and their application to classification, recommendation, and content understanding problems

Requirements

Management and mentorship skills

• Experience managing cross-functional stakeholders with competing priorities
• 1+ years of experience leading machine learning engineering teams
• Bachelor’s in a related technical field such as computer science or equivalent years of experience
• 8+ years of post-Bachelor’s ML industry experience; or a Master’s degree in a technical field + 7+ year of post-grad ML experience; or a PhD in a related technical field + 4+ years of post-grad ML experience
• Experience in ads integrity, content moderation, or trust and safety

Experience with fraud, risk, or abuse detection

• Experience building agentic systems or LLM-based workflows in production
• Experience with large-scale web crawling or URL and content understanding
• Experience with multimodal models across image, video, and text
• Experience with frameworks such as PyTorch or TensorFlow

Preferred

• Experience with ads or marketplace recommendation systems
• Experience with ML platform infrastructure such as distributed batch processing, workflow orchestration, and observability

Pay

USD 229,000 - 343,000