Machine Learning Engineer, Monetization Engineering
$163,418–$285,982 year
Hybrid · San Francisco, California, United States or Palo Alto, California, United States
Job Summary
In the role of Machine Learning Engineer within the Monetization ML Engineering team, you will develop and execute a vision for enhancing the machine learning technology stack primarily for Ads. Responsibilities include building advanced technology utilizing deep learning and machine learning for personalization, collaborating with teams to improve ML models across various product surfaces, and applying data-driven methods for candidate retrieval improvements. Required qualifications include 2+ years of machine learning experience, a degree in a related field, hands-on experience with data processing pipelines, large scale ML systems, and knowledge of recommender systems or modern ads ranking.
Required Qualifications
- 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, machine learning, statistics, or related field
- 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
Desired Qualifications
- 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
Additional Requirements
- US based applicants only
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