Senior Machine Learning Engineer, Advertiser Growth

Unity Technologies SF is hiring a Senior Machine Learning Engineer for the Advertiser Growth team in Olympia, WA (onsite). This role focuses on building technical systems that support advertiser budget pacing, GenAI-driven creative generation, marketplace experimentation, billing reliability, and scientific optimization, with a direct impact on marketplace growth and financial integrity. The compensation range for the position is USD 165,600 - 273,400 per year, with zone-based specifics listed below.

What you’ll be working on

• Design and optimize pacing controllers (including PID and probabilistic forecasting) to smooth advertiser spend across diverse time zones and traffic spikes, supporting optimal delivery and marketplace stability.
• Lead backend integration of Generative AI models such as Diffusion and LLMs to automate the creation of high-performing image and video assets aligned to campaign goals and formats.
• Build and scale infrastructure for high-velocity experimentation including A/B testing, switchback tests, and long-term holdouts to evaluate how marketplace changes affect advertiser ROI and overall platform health.
• Architect and maintain high-throughput billing pipelines processing billions of events with 100% accuracy, connecting real-time ad delivery to mission-critical financial reconciliation.
• Analyze complex financial and marketplace datasets to refine trade-offs between spend velocity and advertiser performance, using experimentation results to tune pacing and billing logic.

What you bring

• Advanced degree in computer science or a relevant engineering field (or equivalent experience).
• 6+ years of software engineering experience, including 3+ years working on ads delivery systems.
• Extensive experience building and operating large-scale, low-latency backend systems using Java, Go, or Scala.
• Deep familiarity with budget control systems, feedback loops, and spend-prediction algorithms.
• Proven experience building or scaling experimentation platforms, including expertise in variance reduction, interference/network effects, and metric design in a marketplace context.
• A track record working on mission-critical pipelines (for example: billing, payments, or clearinghouses) where data precision, idempotency, and fault tolerance are required.
• Experience or strong interest in backend workflows to serve, scale, and store GenAI models for creative asset generation.
• Proficiency with real-time stream processing (such as Kafka, Flink, or Spark) applied to event-based charging and real-time performance feedback.
• Ability to lead complex multi-quarter technical roadmaps and mentor senior engineers in a high-growth environment.
• Sufficient knowledge of English for professional verbal and written communication with colleagues and partners worldwide.

Technologies you’ll use

PID, probabilistic forecasting, Diffusion, LLMs, A/B testing, switchback tests, long-term holdouts, Java, Go, Scala, Kafka, Flink, Spark

Compensation and equity

Zone A: $210,300 - $273,400 USD
Zone B: $187,200 - $243,300 USD
Zone C: $165,600 - $215,200 USD

Beyond base salary, this role may be eligible for equity awards and participation in company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount depends on geographic location and the candidate’s relevant experience, professional background, and skill set.

Benefits

• Comprehensive health, life, and disability insurance
• Commute subsidy
• Employee stock ownership
• Competitive retirement/pension plans
• Generous vacation and personal days
• Support for new parents through leave and family-care programs
• Office food snacks
• Mental Health and Wellbeing programs and support
• Employee Resource Groups
• Global Employee Assistance Program
• Training and development programs
• Volunteering and donation matching program

Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

Additional note

You might also have experience embracing AI as a strategic advantage in engineering, following established best practices for code quality and security.