Senior Machine Learning Engineer (Advertiser Growth)

Join our team as a Senior Machine Learning Engineer focused on Advertiser Growth. In this role, you will lead the design of optimization algorithms that automate campaign optimization for advertisers. You will bridge advanced quantitative methodology and large-scale engineering, working on multi-objective optimization, exploration-exploitation trade-offs, long-term value measurement, and LLM-powered agentic systems. You will also serve as a technical authority and cross-functional leader, ensuring quantitative rigor from model design through live production auctions.

- Conception et mise en œuvre d'algorithmes d'optimisation pour maximiser les performances des campagnes publicitaires. - Développement de méthodologies pour mesurer l'impact à long terme des changements de modèle et de produit. - Leadership technique et collaboration avec des équipes interfonctionnelles pour garantir la rigueur quantitative.

- Experience in machine learning, data science, or applied research, ideally within ad tech, marketplaces, or other large-scale optimization domains - Agentic system experience: Hands-on experience building LLM-based agentic systems - tool use, orchestration, retrieval over domain data, and evaluation of agent quality - ideally applied to diagnostics, recommendations, or workflow automation - Technical proficiency: Strong programming skills in Python or Scala, and experience with large-scale data processing frameworks such as Spark, Snowflake, or BigQuery - Quantitative depth: The skills to design algorithms that optimize among competing goals, design exploration-exploitation strategies balancing short-term and long-term value, build efficient methodologies for measuring long-term impact, and define metrics frameworks that guide launch decisions - Advanced education: An MS or PhD in a quantitative field (Computer Science, Statistics, Operations Research, Economics, or equivalent) - Strategic leadership: Ability to translate complex quantitative concepts into clear product roadmaps and mentor engineers on modeling and optimization rigor - Production track record: A history of shipping ML systems that operate on high-volume, real-time data and delivering measurable business impact - Prior experience with dynamic ads or creative optimization. E.g., dynamic creative assembly, creative ranking and selection, or generative creative pipelines - Hands-on experience with bidding, pricing, pacing, or auction systems in digital advertising - Familiarity with long-term value (LTV) prediction and surrogate metric design in mobile gaming or digital advertising - Experience fine-tuning or evaluating LLMs, or building multi-agent orchestration frameworks - Experience with reinforcement learning or contextual bandits in production