ML Engineering Manager, Identity & Conversion (Hybrid)

Pinterest; Washington; Hybrid; USD 190,000 - 389,000; Full time

Benefits offered by this job

Equity

Hybrid work model

Job summary

Pinterest in the United States is seeking a Machine Learning Engineering Manager to lead a hybrid team of ML and backend engineers, delivering end-to-end identity and conversion visibility solutions across the ads stack.

You will set technical direction for modeling, data pipelines, serving, and measurement, partnering with product managers and data scientists to translate business needs into scalable, reliable systems. Hybrid work.

Qualifications

• 7+ years building and deploying large-scale ML systems in production.
• 2+ years as an engineering manager or technical lead.
• Bachelor's degree in computer science, statistics, or a related field, or equivalent experience.
• Nice to have: experience with ads conversion attribution, identity matching, ads ranking or ads measurement domains.
• Proven technical leadership across ML and software systems with multi-quarter roadmaps.
• Excellent cross-functional communication with product, data science, infra, and partner ML teams.

Responsibilities

• Attract, hire, and lead a hybrid team of ML engineers and backend software engineers.
• Lead strategy, execution, and operational excellence of identity and conversion signal modeling systems.
• Partner with product managers, data scientists, and tech leads to shape problem definitions and drive execution.
• Collaborate with Ads Ranking & Bidding, Measurement Products, and Conversion Ingestion & Attribution teams to define interfaces and success metrics.
• Establish engineering best practices across ML and backend development, including data quality, pipelines, evaluation, and reliability.
• Use AI to accelerate analysis and iteration on model ideas and architectures.

Skills

ML systems

Engineering leadership

Cross-functional collaboration

Education

Bachelor's degree in CS/Statistics

Job description

Pinterest in the United States is seeking a Machine Learning Engineering Manager to lead a hybrid team of ML and backend engineers, delivering end-to-end identity and conversion visibility solutions across the ads stack.

You will set technical direction for modeling, data pipelines, serving, and measurement, partnering with product managers and data scientists to translate business needs into scalable, reliable systems. Hybrid work.