Senior Machine Learning Engineer, Advertiser Growth

Unity Unity · Enterprise · San Francisco, CA · AI & Machine Learning

Senior Machine Learning Engineer role focused on building GenAI systems for creative asset generation, designing budget pacing algorithms, and developing marketplace experimentation infrastructure within Unity's ad-tech ecosystem. The role also involves ensuring high-scale billing reliability and scientific optimization of advertiser spend and performance.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.

Skills

Required

  • Advanced degree in computer science or relevant engineering-related field or equivalent experience
  • 6+ years of software engineering experience
  • 3+ years 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

What the JD emphasized

  • mission-critical
  • zero-fault tolerance
  • 100% accuracy
  • rigorous experimentation frameworks
  • high-velocity experimentation
  • mission-critical pipelines
  • data precision, idempotency, and fault tolerance are paramount

Other signals

  • GenAI systems for creative generation
  • budget pacing algorithms
  • marketplace experimentation infrastructure
  • high-scale billing reliability