Senior Machine Learning Developer, Advertiser Growth

Unity Unity · Enterprise · New York, NY · AI & Machine Learning

Senior Machine Learning Developer for Advertiser Growth at Unity, focusing on building GenAI systems for creative asset generation, optimizing budget pacing algorithms, developing experimentation infrastructure, and ensuring high-scale billing reliability within the ad-tech ecosystem.

What you'd actually do

  1. 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.
  2. 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.
  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

  • 4+ years of software engineering experience
  • 1+ year working on ads delivery systems
  • building and operating large-scale, low-latency backend systems
  • building or maintaining budget control systems, feedback loops, or spend-prediction algorithms
  • building or scaling experimentation platforms
  • working on "mission-critical" pipelines (like billing, payments, or clearinghouses)
  • building the backend workflows required to serve, scale, and store Generative AI models for creative asset generation
  • real-time stream processing (Kafka, Flink, or Spark)
  • lead complex, multi-quarter technical roadmaps
  • mentor senior engineers

Nice to have

  • Experience embracing AI as a strategic advantage in engineering

What the JD emphasized

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

Other signals

  • GenAI systems for creatives
  • budget pacing algorithms
  • experimentation infrastructure
  • high-scale billing pipelines