Sr. Principal Machine Learning Engineer

What you'll do

• Define and execute long-term research strategy for optimization, targeting, bidding, forecasting, and marketplace systems
• Lead a global team of research scientists and applied researchers across multiple geographies
• Identify emerging opportunities in machine learning, AI, optimization, and computational economics
• Foster a culture of scientific rigor, innovation, experimentation, and measurable business impact
• Drive development of large-scale machine learning systems for prediction, recommendation, targeting, and campaign optimization
• Advance state-of-the-art approaches in predictive modeling, reinforcement learning, causal inference, auction theory, multi-objective optimization, control systems, and operations research
• Oversee research from problem formulation through experimentation, deployment, and production monitoring
• Lead innovation across DSP optimization, campaign delivery, supply optimization, and audience targeting systems
• Partner with Product and Engineering leaders to align research investments with strategic business objectives
• Develop frameworks that improve advertiser outcomes, platform efficiency, and marketplace health
• Recruit, mentor, and retain top-tier scientific talent
• Establish technical standards, research processes, and career development frameworks
• Build collaborations across research, engineering, product, and commercial organizations
• Represent the company externally through publications, patents, industry conferences, and academic partnerships
• Translate advanced research into measurable improvements in revenue, efficiency, customer performance, and platform scalability
• Drive data-driven decision-making through experimentation and causal measurement frameworks
• Evaluate strategic technology investments and emerging opportunities

Requirements

• Ph.D. in Electrical Engineering, Computer Science, Operations Research, Applied Mathematics, Statistics, Economics, or related quantitative field
• 15+ years of experience developing machine learning and optimization systems
• 10+ years of leadership experience managing research scientists and technical organizations
• Demonstrated success deploying research innovations into production environments at scale
• Deep expertise in machine learning, optimization, operations research, control theory, economics and auction design, statistical modeling, large-scale experimentation
• Track record of publications, patents, or significant scientific contributions
• Exceptional communication and executive stakeholder management skills
• Experience leading research organizations within digital advertising, marketing technology, marketplaces, or internet-scale platforms
• Expertise in demand-side platforms (DSPs), bidding systems, targeting technologies, or advertising optimization
• Experience managing globally distributed teams
• Strong record of academic and industry thought leadership
• Consistent exercise of independent judgment and discretion in matters of significance
• Regular, consistent and punctual attendance; must be able to work nights and weekends, variable schedule(s) as necessary

Tech stack

Benefits