Senior Machine Learning Engineer, Advertiser Growth

Unity Technologies SF•Mountain View, CA

About The Position

Unity's Advertiser Growth team uses artificial intelligence and statistical optimization to maximize returns and reduce effort for advertisers running campaigns on the Unity ad network. The Senior Machine Learning Engineer will lead the design of optimization algorithms that automate campaign decisions about bids, budgets, and targeting to serve advertiser goals with minimal manual effort. The role bridges advanced quantitative methodology and large-scale engineering, addressing multi-objective optimization, exploration–exploitation trade-offs, long-term value measurement, and LLM-powered agentic systems in real-time production systems. The role includes designing and shipping algorithms that optimize for advertiser goals such as installs, return on ad spend, retention, and spend efficiency while accounting for budgets and marketplace constraints. It also entails developing exploration–exploitation strategies, measuring the long-term effects of model and product changes, establishing metrics frameworks for launch decisions, and building LLM agent systems for campaign diagnostics and setup recommendations. The engineer will serve as a lead subject matter expert for ML, Product, and Engineering partners, maintaining quantitative rigor from model design through live production auctions.

Requirements

Experience in machine learning, data science, or applied research, ideally in ad tech, marketplaces, or other large-scale optimization domains.
An MS or PhD in a quantitative field such as Computer Science, Statistics, Operations Research, or Economics, or equivalent.
Ability to design algorithms for competing goals, exploration–exploitation strategies balancing short- and long-term value, long-term impact measurement methodologies, and metrics frameworks for launch decisions.
Hands-on experience building LLM-based agentic systems, including tool use, orchestration, retrieval over domain data, and evaluation of agent quality; experience in diagnostics, recommendations, or workflow automation is ideal.
Strong programming skills in Python or Scala.
Experience with large-scale data processing frameworks such as Spark, Snowflake, or BigQuery.
A track record of shipping ML systems that operate on high-volume, real-time data and deliver measurable business impact.
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, such as 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

Design and ship algorithms that optimize campaigns across advertiser goals—including installs, ROAS, retention, and spend efficiency—under budget and marketplace constraints.
Design exploration–exploitation strategies, such as bandits or reinforcement learning, that balance short-term performance with long-term value.
Develop efficient methods to measure the long-term impact of model and product changes, including surrogate metrics that provide short-term signals for long-term advertiser and user value.
Define metrics frameworks and clear criteria that connect model improvements to advertiser outcomes and business results and guide launch decisions.
Build LLM agent systems that automate campaign diagnostics and setup recommendations by analyzing performance, identifying root causes, and recommending or applying configuration changes.
Serve as a lead subject matter expert for ML, Product, and Engineering partners, ensuring quantitative rigor from model design through live production auctions.
Translate complex quantitative concepts into clear product roadmaps and mentor engineers on modeling and optimization rigor.

Benefits

Comprehensive health, life, and disability insurance.
Commute subsidy.
Employee stock ownership.
Competitive retirement or pension plans.
Generous vacation and personal days.
Leave and family-care programs supporting new parents.
Office food and snacks.
Mental health and wellbeing programs and support.
Employee Resource Groups.
Global Employee Assistance Program.
Training and development programs.
Volunteering and donation matching program.
The role may be eligible for equity awards and participation in company incentive plans, such as annual discretionary bonuses or sales commissions.