Sr. Machine Learning Engineer, Monetization Engineering

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Company Overview

A leading global visual discovery and inspiration platform connects hundreds of millions of users with creative ideas, products, and possibilities. The organization uses artificial intelligence and machine learning to create personalized experiences, helping users discover relevant content while enabling partners to reach audiences through innovative advertising and commerce solutions.

With a global workforce of more than 4,000 employees and a vast repository of user-generated ideas and engagement data, the organization provides machine learning engineers with opportunities to work on large-scale recommendation systems, personalization technologies, and data-driven products.

The organization is seeking a Sr. Machine Learning Engineer, Monetization Engineering to help evolve the machine learning technology stack supporting advertising and monetization products. This role will focus on developing advanced machine learning solutions that connect user interests and aspirations with products and services offered by partners.

The successful candidate will work closely with teams across the organization to develop, experiment with, and improve machine learning models across multiple product surfaces, including Homefeed, Ads, Growth, Shopping, and Search. The role provides an opportunity to work with large-scale datasets, recommendation systems, deep learning technologies, and emerging AI capabilities.

Key Responsibilities

• Build cutting-edge machine learning and deep learning technologies to deliver personalized user experiences.
• Partner with teams across the organization to experiment with and improve machine learning models across various product surfaces.
• Develop data-driven methods that leverage unique data characteristics to improve candidate retrieval and ranking.
• Design, build, and optimize large-scale machine learning systems and data processing pipelines.
• Contribute to rapid experimentation, product launches, and high-impact machine learning initiatives.
• Research and apply emerging techniques in recommendation systems and personalization.
• Leverage Large Language Models (LLMs) to enhance content understanding and machine learning capabilities.
• Help define and execute the vision for the evolution of the machine learning technology stack within advertising and monetization.
• Collaborate with engineering, product, data science, and other cross-functional teams to deliver scalable machine learning solutions.
• Stay current with developments and emerging trends in machine learning, recommendation systems, and computational advertising.
• Apply AI-powered development tools to improve engineering productivity, debugging, testing, documentation, and software development workflows.

Required Qualifications

• 2+ years of industry experience applying machine learning methods such as user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, or graph representation learning.
• Bachelor’s degree in Computer Science, Statistics, or a related field, or equivalent professional experience.
• End-to-end hands-on experience building data processing pipelines and large-scale machine learning systems.
• Experience working with big data technologies such as Hadoop and Spark.
• Practical knowledge of large-scale recommender systems, modern advertising ranking and retrieval, targeting, or marketplace systems.
• Strong understanding of machine learning concepts and their practical application to large-scale products.
• Ability to collaborate effectively with cross-functional teams and communicate technical concepts clearly.

Preferred Qualifications

• Master’s degree or PhD in Machine Learning or a related field.
• Publications at leading machine learning conferences.
• Experience using AI coding assistants such as Cursor, Copilot, Codex, or similar tools for development, debugging, testing, and refactoring.
• Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL and data exploration, and engineering workflow acceleration.
• Expertise in scalable real-time systems that process streaming data.
• Background in computational advertising.
• Passion for applied machine learning and consumer-facing products.
• Experience working with personalization, recommendation, ranking, retrieval, or advertising systems at significant scale.

Disclaimer

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