Senior Machine Learning Engineer (Ads Optimization)

Join Reddit as a Senior Machine Learning Engineer in the Ads Optimization team. You'll design and implement optimization algorithms for auctions, bidding strategies, and pacing, while owning systems end-to-end. Collaborate closely with Product, Data Science, and Infra partners across Reddit Ads.

• 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.
• Lead more complex or multi-quarter initiatives, set technical direction for key parts of the bidding/auction/pacing stack, and mentor other engineers while remaining hands-on.

• (Level will be determined during the interview process; IC4 expectations assume deeper experience and broader scope.)
• Degree or equivalent background in a quantitative field (math, physics, quantitative finance, economics, operations research, or similar)
• 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
• 3–5+ years of experience building, deploying, and operating machine learning systems in production (for IC4, typically 5+ years)
• Work experience in optimization-heavy domains (e.g., bidding/auctions, pacing, pricing, logistics optimization, quantitative finance)
• Strong programming skills in Python, Java, Go, or similar languages, with solid software engineering fundamentals
• Evidence of stronger math and optimization skills than a generic MLE, such as:
• 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
• Experience collaborating with cross-functional partners (Product, DS, Eng) in Ads or marketplace contexts and leading projects from design through rollout
• Background in feature engineering, model optimization, and production monitoring for ML systems
• Advanced degree (MS or PhD) in Computer Science, Machine Learning, Operations Research, Applied Math, or a related quantitative field
• Additional expectations for strong bidding/auction candidates: