Software Engineer, Monetization ML Infrastructure

Details

The Monetization team is a cross-functional group working across engineering, product, research, and design to build foundational systems for scaling access to intelligence responsibly. Its mission includes developing user-first, privacy-preserving monetization products, including next-generation advertising experiences, while upholding user trust, privacy, safety, and ecosystem health.

The role focuses on building the machine learning infrastructure that powers OpenAI's monetization and advertising systems. This includes platform capabilities for building, training, deploying, serving, monitoring, and continuously improving machine learning models across the full ML lifecycle. The systems must support high-throughput, low-latency workloads while meeting strict requirements for reliability, privacy, security, and performance.

Responsibilities

• Design and build ML infrastructure for monetization and advertising systems.
• Develop large-scale data pipelines processing impressions, clicks, conversions, advertiser data, marketplace signals, and other model-training inputs.
• Create scalable model-training platforms for ranking, conversion prediction, quality prediction, bidding, targeting, measurement, and optimization workloads.
• Develop systems that safely and reliably move models from experimentation into production.
• Build and improve real-time inference and model-serving infrastructure with strict latency, throughput, reliability, and availability requirements.
• Design experimentation frameworks for A/B testing, holdouts, model comparisons, ramping strategies, and large-scale measurement.
• Optimize training efficiency, inference latency, model throughput, infrastructure reliability, and cost effectiveness.
• Collaborate with machine learning engineers, product engineers, data scientists, and monetization teams to accelerate the development and deployment of advertising systems.

Requirements

• 7+ years of professional software engineering experience building large-scale distributed systems or machine learning infrastructure.
• Experience building platforms that support machine learning workflows, including data processing, feature engineering, model training, deployment, or serving.
• Experience working with high-volume data pipelines and infrastructure for large-scale online systems.
• Experience designing reliable, low-latency systems with strong operational and observability practices.
• Comfort working across the ML lifecycle, from data and training systems through deployment, experimentation, and monitoring.
• Experience improving infrastructure performance, scalability, efficiency, and reliability in production environments.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. OpenAI is an equal opportunity employer and provides reasonable accommodations to applicants with disabilities. Background checks are administered in accordance with applicable law.