Sr. Machine Learning Engineer, Monetization Engineering

About the role

You will architect and implement advanced machine learning systems that directly influence the monetization strategy of one of the world's largest visual discovery platforms. This role owns the end-to-end lifecycle of high-impact ML features within the Ads monetization stack, from data modeling and retrieval to production deployment and experimentation. You will act as a key technical partner for product and engineering teams, driving innovation in personalized experiences that connect Pinners with relevant content from our partners. Your work will leverage large language models and deep learning to extract nuanced understanding from content and intent. You will operate in a fast-paced, data-rich environment where rigorous analysis meets rapid product execution. Collaboration across diverse teams will be central to your success as you help define the future of AI-driven monetization.

Key facts

What you'll do

Architect and deploy scalable machine learning models that optimize advertising relevance and performance across Pinterest's core product surfaces.

Partner with cross-functional teams including Product, Data Science, and Infrastructure to design experiments that validate hypotheses and improve ML models for Homefeed, Ads, Growth, Shopping, and Search.

Develop and maintain data processing pipelines that leverage the unique properties of Pinterest data to enhance candidate retrieval and targeting accuracy.

Lead the integration of large language models to advance content understanding, entity recognition, and semantic matching within monetization workflows.

Conduct rigorous analysis of model performance using statistical methods and A/B testing to inform iterative improvements and strategic decisions.

Collaborate with researchers and engineers to stay current with industry trends in recommendation systems, real-time learning, and large-scale modeling.

Implement solutions that operate efficiently in high-impact, high-availability environments supporting quick experimentation and rapid product launches.

Define and own technical roadmaps for the ML stack within the Ads organization, ensuring alignment with Pinterest's long-term product vision.

Requirements

2+ years of industry experience applying machine learning methods such as user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning.

Degree in computer science, statistics, or a related field; or equivalent practical experience.

Hands-on expertise in building data processing pipelines and large-scale machine learning systems using big data technologies such as Hadoop and Spark.

Demonstrated proficiency in developing and deploying large-scale recommender systems or modern advertising ranking, retrieval, targeting, and marketplace systems.

Strong programming skills in languages commonly used for ML engineering, including Python and SQL, with experience in model training and deployment workflows.

Practical knowledge of scalable real-time systems that process streaming data and support low-latency inference in production.

Ability to communicate complex technical concepts to both technical and non-technical stakeholders and influence without direct authority.

Willingness to engage in the company's interview process which includes evaluating how candidates use AI tools in their work.

Nice to have

Master of Science or PhD in Machine Learning, Computer Science, or a closely related quantitative field.

Publications at premier academic or industry conferences in machine learning or related domains.

Experience using AI-assisted development tools such as Cursor, GitHub Copilot, or Amazon CodeWhisperer for coding, debugging, testing, and refactoring.

Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL exploration, and engineering workflow acceleration.

Expertise in building and operating scalable real-time systems that process streaming data at high throughput.

A demonstrated passion for applied machine learning and deep engagement with the Pinterest product and community.

Background in computational advertising, including experience with marketplaces, bidding, and attribution modeling.

Practical notes

This is a full-time position located in the United States.

Eligible candidates must be authorized to work in the United States without sponsorship for this role.

Relocation is not supported for this position.

Travel is not expected for this role.

Interviews may include the use of AI tools as part of the evaluation process.