Senior Machine Learning Engineer, Advertiser Intelligence

Unity Technologies•Mountain View, CA

1d•$159,100 - $238,700

About The Position

Unity's Advertiser Growth team leverages artificial intelligence and statistical optimization to maximize returns and reduce effort for advertisers running campaigns on the Unity ad network. Our ads reach billions of devices, and every improvement we ship directly moves outcomes for thousands of advertisers worldwide. We are looking for a senior Machine Learning Engineer to lead the design of the optimization algorithms at the heart of this mission. In this role, you will be a technical authority on how we automate campaign optimization: how bids, budgets, and targeting decisions are made to serve each advertiser's goals with minimal manual effort. You will bridge advanced quantitative methodology and large-scale engineering, working where multi-objective optimization, exploration–exploitation trade-offs, long-term value measurement, and LLM-powered agentic systems meet real-time production systems.

Requirements

5+ years in machine learning, data science, or applied research, ideally within ad tech, marketplaces, or other large-scale optimization domains.
An MS or PhD in a quantitative field (Computer Science, Statistics, Operations Research, Economics, or equivalent).
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.
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.
Production track record: A history of shipping ML systems that operate on high-volume, real-time data and delivering measurable business impact.
Strategic leadership: Ability to translate complex quantitative concepts into clear product roadmaps and mentor engineers on modeling and optimization rigor.

Nice To Haves

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 with reinforcement learning or contextual bandits in production.
Experience fine-tuning or evaluating LLMs, or building multi-agent orchestration frameworks.

Responsibilities

Multi-objective campaign optimization: Design and ship algorithms that optimize across a variety of advertiser goals — installs, ROAS, retention, and spend efficiency — under real-world budget and marketplace constraints.
Exploration–exploitation strategy: Design strategies (e.g., bandits, reinforcement learning) that balance short-term performance against long-term value, so campaigns learn efficiently without sacrificing advertiser returns.
Long-term impact measurement: Develop efficient methodologies to measure the long-term impact of model and product changes, including surrogate metrics that give short-term signals for long-term advertiser and user value.
Metrics frameworks for launch decisions: Define the metrics frameworks that guide what we ship — clear, trustworthy criteria that connect model improvements to advertiser outcomes and business results.
Agentic automation for advertisers: Build LLM agent systems that automate campaign diagnostics and setup recommendations — agents that analyze campaign performance, identify root causes and recommend or apply configuration changes, so advertisers state their goals and trust the system to deliver.
Cross-functional technical leadership: Serve as a lead subject matter expert for ML, Product, and Engineering partners, ensuring quantitative rigor from model design through live production auctions.