Sr. Machine Learning Engineer, Monetization Engineering

Pinterest • San Francisco, CA

10d • Hybrid

About The Position

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else. Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.

Requirements

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• Degree in computer science, statistics, or related field; or equivalent experience
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems

Nice To Haves

• M.S. or PhD in Machine Learning or related areas
• Publications at top ML conferences
• Expertise in scalable realtime systems that process stream data
• Passion for applied ML and the Pinterest product
• Background in computational advertising

Responsibilities

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest Partner
• Closely partner with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keep up with industry trends in recommendation systems
• Leverage LLMs to enhance content understanding

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level