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Senior Machine Learning Engineer (Advertiser Growth)

Unity

Skills

Required

  • machine learning / data science / applied research
  • orchestration
  • digital advertising
  • ad tech
  • marketplaces
  • LLM-based
  • retrieval
  • evaluation of agent quality
  • workflow automation
  • programming
  • Python / Scala
  • data processing frameworks
  • Spark / Snowflake / BigQuery
  • dynamic ads

Preferred

  • LTV
  • prediction
  • surrogate metric design
  • mobile gaming
  • fine-tuning
  • LLMs
  • multi-agent orchestration frameworks
  • reinforcement learning / contextual bandits in production
  • algorithms
  • design exploration-exploitation strategies

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.

Advanced education: An MS or PhD in a quantitative field (Computer Science, Statistics, Operations Research, Economics, or equivalent)

About Unity

Production track record: A history of shipping ML systems that operate on high-volume, real-time data and delivering measurable business impact

Responsibilities

  • 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.
  • 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

Requirements

  • 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
  • Strategic leadership: Ability to translate complex quantitative concepts into clear product roadmaps and mentor engineers on modeling and optimization rigor
  • 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

Preferred

  • 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

Pay

USD 148,700 - 244,600