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About the Role
Pinterest's Ads Quality organization builds machine-learning systems to enhance ad relevance and value for users, while driving positive outcomes for advertisers. This role will lead a diverse group of Ads Quality modeling teams focused on key areas like engagement, conversion, ROAS optimization, ranking, representation learning, and ML-powered experimentation.
Responsibilities
- Set the technical vision and multi-year strategy for Ads Quality machine learning, connecting model innovation to Pinner value, advertiser performance, revenue, and marketplace health.
- Lead and develop a group of engineering managers, senior technical leaders, and machine-learning engineers across multiple modeling domains.
- Establish a coherent modeling roadmap across engagement, conversion, ROAS, relevance, ranking, and foundation-model initiatives.
- Drive improvements in model quality, calibration, generalization, cold-start performance, attribution, and robustness across Pinterest surfaces.
- Guide the evolution of Ads models toward larger, more generalizable architectures, including foundation models, distillation, long-context sequence modeling, multimodal representations, and cross-domain learning.
- Ensure that modeling investments translate into reliable production outcomes through strong offline evaluation, online experimentation, launch discipline, and post-launch monitoring.
- Partner closely with Ads Product, Ads Data Science, Ads Signals, Ads Retrieval, Ads Delivery, Measurement, Core, ATG, and ML Infrastructure.
- Set expectations for training-serving parity, data quality, privacy, reliability, latency, capacity, and cost efficiency.
- Improve engineering velocity through better experimentation workflows, reusable modeling infrastructure, automation, and agentic development tools.
- Build a culture of technical excellence, candid collaboration, inclusion, ownership, and continuous learning.
- Represent Ads Quality ML in senior leadership forums and communicate strategy, tradeoffs, risks, and results clearly to technical and non-technical audiences.
Requirements
- Minimum 12 years of experience building and deploying machine-learning systems, including significant experience leading managers and multi-team organizations.
- Demonstrated success leading large-scale recommendation, ranking, advertising, search, marketplace, or personalization ML teams.
- Strong understanding of modern deep-learning and recommender-system techniques, including sequence models, embeddings, multimodal models, multi-task learning, foundation models, distillation, and reinforcement learning.
- Experience with conversion, value, ROAS, bidding, or other lower-funnel optimization problems is strongly preferred.
- Proven ability to connect modeling objectives and offline metrics to online experiments and business outcomes.
- Experience operating production ML systems with demanding requirements for latency, availability, calibration, privacy, reliability, and cost.
- Strong judgment in balancing near-term product delivery with foundational technical investments.
- Track record of building high-performing organizations, developing senior leaders, and creating effective operating mechanisms.
- Excellent communication and collaboration skills, with the ability to influence across organizational boundaries.
Skills
- Deep learning
- Recommender systems
- Sequence models
- Embeddings
- Multimodal models
- Multi-task learning
- Foundation models
- Distillation
- Reinforcement learning
- Conversion optimization
- Value optimization
- ROAS optimization
- Bidding optimization
- Lower-funnel optimization
- Offline evaluation
- Online experimentation
- Production ML systems
- Latency management
- Availability management
- Calibration
- Privacy
- Reliability
- Cost efficiency
Location
- Palo Alto
- San Francisco
Work Type
- Hybrid
Experience Level
- Director
- 12+ years of experience
Education Level
- Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience
- Advanced degree preferred
Salary/Compensations
- $314,580—$550,515 USD
Benefits
- Equity
About the Company
- Pinterest is a visual discovery platform where hundreds of millions of people come to find inspiration and decide what to try, buy, or do next.
- At Pinterest, AI is a powerful partner that augments creativity and amplifies impact.
- Pinterest is committed to fostering a workplace that is equitable, inclusive, and inspiring.
Equal Opportunity
- Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit.
- All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws.
- Pinterest also considers qualified applicants regardless of criminal histories, consistent with legal requirements.
- US based applicants only.