Machine Learning Engineer, Ads Optimization & Ads Marketplace Quality

Reddit, Inc. is a community-driven platform that facilitates open conversations among its users. They are seeking a Machine Learning Engineer to design and implement optimization algorithms for their ads marketplace, focusing on auction mechanisms and ensuring marketplace quality.

Responsibilities:

• Design and implement models and policies that:
• Compute bids for different optimization objectives (e.g., 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 (e.g., ROI, revenue, delivery smoothness, fairness, and user experience)
• Partner with Ads Marketplace Quality to:
• 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
• Collaborate closely with Ads Optimization to integrate new bid strategies and pacing mechanisms into the broader ads ecosystem and measurement stack

Requirements:

• 3–5+ years of experience building, deploying, and operating machine learning systems in production (for IC4, typically 5+ years)
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• Experience designing scalable data processing systems (e.g., Spark, Kafka, Airflow, BigQuery, Redis)
• Demonstrated ability to translate ambiguous product or business problems into solutions and to improve measurable metrics
• Evidence of stronger math and optimization skills than a generic MLE, such as: Degree or equivalent background in a quantitative field (math, physics, quantitative finance, economics, operations research, or similar)
• Work experience in optimization-heavy domains (e.g., bidding/auctions, pacing, pricing, logistics optimization, quantitative finance)
• Comfort reasoning about and implementing custom optimization logic (e.g., gradient-based methods, constraint handling), not just applying black-box tooling
• Experience with advertising/auction systems, online marketplaces, or search/ranking systems at scale, particularly in: Bidding, pacing, or budget optimization; Auction design, mechanism design, or marketplace quality; Campaign performance optimization (e.g., 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 and leading projects from design through rollout
• Advanced degree (MS or PhD) in Computer Science, Machine Learning, Operations Research, Applied Math, or a related quantitative field