Engineering Manager, ML Content & Signals

Engg; United States; Hybrid; USD 223,000 - 390,000; Full time

Benefits offered by this job

Equity

Job summary

Pinterest is seeking an experienced Engineering Manager for the Content Foundation ML Team in the USA. You will lead a team of engineers and applied scientists to build foundational content understanding signals, scalable infrastructure, and model-powered capabilities that power Discovery, Search, Growth, and Ads.

This role requires setting a long-term technical vision for semantic signal generation and collaborating with product, data science, and partner ML teams to deliver impact at scale,

Qualifications

• 7+ years of industry experience, including 2+ years in management.
• Masters degree in computer science, computer engineering, or equivalent work experience.
• Publication at top machine learning and data mining conferences (e.g., NeurIPS, ICML, KDD, SIGIR).
• Experience with large-scale distributed training and inference of LLM and VLM models.
• Proven technical leadership across ML and Data systems, with multi-quarter roadmaps.

Responsibilities

• Lead and mentor engineers and applied scientists in developing foundational content understanding signals, infrastructure and systems.
• Provide long-term technical vision for semantic signal generation and scalable model-powered infrastructure.
• Partner with product, data science, and downstream engineering teams to ensure signals drive impact.
• Manage project execution, roadmap planning, risk mitigation, and stakeholder communication.
• Address challenges in leveraging VLM/LLM technologies and building reusable foundations.

Skills

Management experience

ML leadership

Distributed systems

Cross-functional collaboration

Communication skills

Education

Master's degree

Publications in ML conferences

Tools

Hadoop

Spark

GenAI platforms

Job description

Pinterest is seeking an experienced Engineering Manager for the Content Foundation ML Team in the USA. You will lead a team of engineers and applied scientists to build foundational content understanding signals, scalable infrastructure, and model-powered capabilities that power Discovery, Search, Growth, and Ads.

This role requires setting a long-term technical vision for semantic signal generation and collaborating with product, data science, and partner ML teams to deliver impact at scale,