Manager II, Machine Learning Engineering-Content Foundation

The role

This role manages a team of engineers and applied scientists on the Content Foundation ML team. The group produces reusable semantic signals from Pinterest content that feed several major product surfaces. The manager sets long-term technical direction and coordinates with product, data science, and partner engineering groups.

What you would do

• Grow and direct engineers and applied scientists building shared content-understanding signals and serving infrastructure
• Define a multi-year technical strategy for semantic signal generation and reusable model-driven foundations
• Coordinate with product, data science, and downstream engineering to convert signals into measurable product impact
• Own roadmap planning, technical trade-offs, risk management, and stakeholder updates
• Guide the team through hard problems such as scaling vision-language and language model inference across locales
• Drive monitoring, evaluation, and debugging practices that keep signal quality, latency, and freshness high

What they asked for

• Seven or more years of industry experience, with at least two years leading people
• Master's degree in computer science or computer engineering, or equivalent practical experience
• Publication record at leading machine learning or data mining venues
• Hands-on experience running large-scale distributed training and inference for large language and vision-language models
• Familiarity with distributed data processing for ML pipelines using frameworks such as Hadoop or Spark
• Track record leading ambiguous GenAI projects for content understanding or recommendation systems
• Demonstrated ability to set multi-quarter direction across modeling, data pipelines, and productionization
• Strong communication and cross-functional alignment skills with senior stakeholders