Staff Machine Learning Engineer, Ads Bidding & Pacing

What you'll do

• Develop production code to generate high-quality ad recommendations and improve platform performance.
• Design and build scalable solutions for budget and bid optimization to improve advertiser campaign performance.
• Lead the development and application of advanced machine learning techniques and algorithms for the ad network.
• Perform large-scale and complex experiments to understand the effects of new models and systems.
• Prioritize an innovation roadmap across multiple technical domains based on ad network behavior.
• Lead the conception, development, and delivery of state-of-the-art capabilities that differentiate products.
• Translate research concepts into production-quality code for global-scale systems.

What we're looking for

• 8+ years of experience building machine learning and quantitative optimization capabilities across many different product areas at scale.
• Experience in machine learning, quantitative methods, control systems, or reinforcement learning.
• Ability to apply and implement research concepts into production quality code.
• Experience defining clear, testable research hypotheses with intended business impact.
• Deep knowledge of design of experiments and online experimentation approaches, preferably at scale (preferred).
• Experience contributing to or reviewing research for top conferences and publications.
• Deep fluency in Java or Python.
• Experience with Spark, Hadoop, or other distributed frameworks.
• PhD in Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning, or a related field with production experience.
• Experience in ads optimization, recommendations, or search relevance optimization (preferred).