Staff Machine Learning Engineer

The opportunity

At Unity, we’re committed to building a culture grounded in Empathy, Respect, and Opportunity. Within our fast-paced and collaborative environment, we’re tackling complex challenges that drive meaningful impact for creators and users across our ecosystem. The Unity Demand Optimization team plays a central role in this effort by building ad campaign optimizations that enable advertisers to efficiently capture user engagement while minimizing their costs. The team leverages machine learning models to incorporate advertisers' off-site goals into auction ranking, helping them maximize installs, key conversions, or return on ad spend.

We are seeking a highly skilled staff engineer to take a critical role in building state-of-the-art bidding optimization systems that enable:

• Efficient budget pacing across campaigns.
• Automated bidding strategies that align with advertiser goals.
• Continual system improvement through rigorous experimentation.
• Sustainable growth for Unity’s advertising business.

What you'll be doing

• Design, implement, and maintain high-performance auto-bidding algorithms and advertiser-facing products (e.g., Target ROAS, Target CPA).
• Ensure these systems meet or exceed campaign performance goals, advertiser expectations, and system reliability standards.
• Lead development on core initiatives such as:
• A bid-based budget pacing system that ensures daily budget delivery.
• Maximize Conversions, which leverages real-time bidding to meet key advertiser goals.
• Lowest Cost, a product that automates bidding to simplify campaign management.
• Target ROAS, which lets advertisers scale volume without sacrificing performance targets.
• Drive best practices for model quality, experimentation, system reliability, and operational excellence.
• Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
• Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

• Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, or a related field—or equivalent practical experience.
• 5+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
• 3+ years of experience building control systems, PID controllers, multi-armed bandits, reinforcement learning algorithms, or bid/pricing optimization systems.
• Significant experience in one or more general-purpose programming languages like Java, Python, Go, Scala, C++ or similar.
• Knowledge of metric design, experimentation methodologies, and large-scale data analysis.
• Plus) Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
• Plus) Experience with state of the art control systems, reinforcement learning algorithms.