Sr. Staff Machine Learning Engineer, Ads Quality

Sr. Staff Machine Learning Engineer, Ads Quality

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Sr. Staff Machine Learning Engineer, Ads Quality

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Pinterest . Within the Ads Ranking team, you will develop and execute a vision for the evolution of the machine learning technology stack for the conversion modeling team. Your responsibilities include tackling challenges such as user sequence modeling, embedding features, model quantization, utility alignment, RoAS optimization, and more to enhance ML models powering the heavy ranker stage and delivery, connecting pinners and partners in this marketplace. What You’ll Do

Lead the technical direction and develop state-of-the-art applied machine learning projects for the ads conversion modeling team. Coach and mentor engineers within the team. Design features and build large-scale machine learning models to improve user ad action prediction with low latency. Develop new techniques for inferring user interests from online activity. Mine text, visual, and user signals to better understand user intentions. Collaborate with product and sales teams to design and implement new ad products. What We’re Looking For

MS or PhD in Computer Science, Statistics, or related field. 6+ years of experience building production ML systems at scale, data mining, search, recommendations, or NLP. 2+ years of experience leading projects or teams. Strong mathematical skills with knowledge of statistical methods. Excellent cross-functional collaboration and communication skills. Background in computational advertising is preferred but not required. Additional Details

This role requires in-office collaboration 1-2 times/month and can be located anywhere in the country. It is not eligible for relocation assistance. The salary range is $250,545—$438,454 USD, and the position is eligible for equity. Final salary depends on experience, location, and skills. At Pinterest, we are committed to inclusion and equal opportunity employment. We welcome applicants regardless of race, gender, religion, or background, and provide accommodations during the application process.

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