Senior Machine Learning Engineer, Ads Optimization

Reddit is a community of communities built on shared interests, passion, and trust, and one of the internet’s largest sources of information. The Senior Machine Learning Engineer will build and evolve auction, bidding, budgeting, and pacing systems for Reddit Ads, owning initiatives from algorithm design through production deployment while collaborating with Product, Data Science, and Infrastructure teams.

Responsibilities:

• Design and implement optimization algorithms for auctions, bidding strategies, and pacing that balance advertiser performance, user experience, and marketplace efficiency
• 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) to deliver measurable wins for advertisers and Redditors
• 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)

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
• 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