Machine Learning Engineer, Ads Optimization & Ads Marketplace Quality

Responsibilities

Auction, Bidding, and Pacing Systems

• Design and implement models and policies that compute bids for different optimization objectives (CPC, CPA, ROAS-based strategies).
• Pace budgets smoothly over time across accounts, campaigns, and ad groups while preventing overspend or underspend.
• Allocate spend and auction participation intelligently across segments, surfaces, and time zones.
• Translate product and marketplace goals into concrete optimization problems and constraints (ROI, revenue, delivery smoothness, fairness, user experience).

Marketplace Quality and Optimization

• Improve ad matching and ranking by incorporating new quality and relevance signals into bidding and auction decisions.
• Inform policies around ad load and eligibility that protect user experience while increasing high-quality ad opportunities.
• Integrate new bid strategies and pacing mechanisms into the broader ads ecosystem and measurement stack.

General

• Own systems end-to-end: from problem formulation and algorithm design to experimentation, production deployment, and ongoing iteration.
• Work across Ads Optimization (bid strategies, budget optimization, pacing) or Ads Marketplace Quality (ad matching, ad load, quality controls).

Requirements

• 3–5+ years of experience building, deploying, and operating machine learning systems in production (5+ years for IC4).
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals.
• Experience designing scalable data processing systems (Spark, Kafka, Airflow, BigQuery, Redis).
• Demonstrated ability to translate ambiguous product or business problems into solutions and improve measurable metrics.
• Evidence of stronger math and optimization skills: degree or equivalent background in a quantitative field (math, physics, quantitative finance, economics, operations research).
• Work experience in optimization-heavy domains (bidding/auctions, pacing, pricing, logistics optimization, quantitative finance).
• Comfort reasoning about and implementing custom optimization logic (gradient-based methods, constraint handling).

Preferred Qualifications

• Experience with advertising/auction systems, online marketplaces, or search/ranking systems at scale.
• Experience in bidding, pacing, budget optimization, auction design, mechanism design, marketplace quality, or campaign performance optimization (CTR/CVR, CPA, ROAS).
• Familiarity with large-scale, real-time decision systems and low-latency production environments.
• Background in feature engineering, model optimization, and production monitoring for ML systems.
• Experience collaborating with cross-functional partners (Product, DS, Eng) in Ads or marketplace contexts.
• Advanced degree (MS or PhD) in Computer Science, Machine Learning, Operations Research, Applied Math, or a related quantitative field.

Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs (workspace, professional development, caregiving support)
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave