Sr. Principal Machine Learning Engineer

Job Summary

We are seeking a Sr Principal Scientist of Research & Optimization Sciences to lead a world‑class organization of research scientists and machine learning experts focused on developing the next generation of optimization, prediction, targeting, and marketplace systems. This executive will define the scientific vision, research agenda, and technical strategy for large‑scale advertising and marketing platforms, driving innovations that directly impact revenue, customer performance, and marketplace efficiency.

The ideal candidate combines deep expertise in machine learning, optimization, economics, operations research, and experimentation with a proven ability to lead globally distributed research organizations. This leader will translate cutting‑edge research into production systems operating at internet scale while partnering closely with Product, Engineering, Data Science, and Business leadership.

• Define and execute the 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, artificial intelligence, 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
  • Operations research
• Oversee research from problem formulation through experimentation, deployment, and production monitoring.

• Lead innovation across demand‑side platform (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.

• 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 several of the following:
  • 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.

• Measurable improvements in platform performance and optimization outcomes.
• Successful deployment of research innovations into production systems.
• Growth and retention of scientific…