Senior Machine Learning Engineer, Advertiser Growth

Unity Technologies
Mountain View, CA, USA / USA-New York, New York, NY, USA2026-05-07

About the job

The Advertiser Growth team is the engine of this mission, ensuring that as our marketplace expands, advertisers have the intelligent tools, robust infrastructure, and rigorous experimentation frameworks needed to scale their impact. This role is unique in its technical breadth, sitting at the intersection of financial execution, creative innovation, and marketplace science. You will architect the GenAI systems that build high-performing creatives, design the pacing algorithms that manage multi-million dollar budgets, ensure our billing pipelines handle massive scale with zero-fault tolerance, and build the experimentation infrastructure that allows us to scientifically evolve the marketplace. This is a high-stakes role where your technical leadership directly governs Unity’s financial integrity and the long-term growth of our ecosystem.

Responsibilities

Next-Gen budget pacing: Design and optimize sophisticated pacing controllers (PID, probabilistic forecasting) to smooth advertiser spend across diverse time zones and traffic spikes, ensuring optimal delivery and marketplace stability.

Creative GenAI infrastructure: Lead the backend integration of Generative AI models (Diffusion, LLMs) to automate the creation of high-performing image and video assets tailored to specific campaign goals and formats.

Marketplace experimentation engine: Build and scale the infrastructure for high-velocity experimentation, including A/B testing, switchback tests, and long-term holdouts to measure the impact of marketplace changes on advertiser ROI and platform health.

High-Scale billing reliability: Architect and maintain high-throughput billing pipelines that process billions of events with 100% accuracy, bridging the gap between real-time ad delivery and mission-critical financial reconciliation.

Scientific optimization: Analyze complex financial and marketplace datasets to refine the trade-off between spend velocity and advertiser performance, using experimentation results to tune pacing and billing logic.

Qualifications

Minimum

Advanced degree in computer science or relevant engineering-related field or equivalent experience.

4+ years of software engineering experience, including 1+ year working on ads delivery systems.

Extensive experience building and operating large-scale, low-latency backend systems using languages like Java, Go, or Scala.

Deep familiarity with building or maintaining budget control systems, feedback loops, or spend-prediction algorithms.

Proven experience building or scaling experimentation platforms, with a deep understanding of variance reduction, interference/network effects, and metric design in a marketplace context.

A track record of working on "mission-critical" pipelines (like billing, payments, or clearinghouses) where data precision, idempotency, and fault tolerance are paramount.

Experience or strong technical interest in building the backend workflows required to serve, scale, and store Generative AI models for creative asset generation.

Proficiency with real-time stream processing (Kafka, Flink, or Spark) specifically applied to event-based charging and real-time performance feedback.

A proven ability to lead complex, multi-quarter technical roadmaps and mentor senior engineers in a high-growth environment.

Preferred

Experience embracing AI as a strategic advantage in engineering, following established best practices for code quality and security.