Software Engineer, Monetization AI/ML (SF/Seattle)

About the Team

The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation.

Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses.

This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale.

About the Role

We’re looking for experienced Software Engineers to help build OpenAI’s foundational ads ranking and recommendation systems—the ML and AI platforms that determine how monetized experiences are selected, ordered, and optimized across OpenAI products.

In this role, you’ll architect and implement large-scale, high-performance ML-driven systems with rigorous requirements around latency, correctness, safety, privacy, and continuous improvement. You’ll work on modern, transformer- and LLM-inspired architectures that move beyond traditional feature engineering toward more expressive, context-aware decisioning. Your work will have a direct revenue impact and make ChatGPT and other products accessible to more people with fewer usage limits or without having to pay.

This is a deeply technical, 0→1 founding-stage role where you’ll operate across backend engineering, systems design, and applied AI/ML to help define the next generation of AI-native monetization and recommendation platforms.

This role is exclusively based across our San Francisco and Seattle sites. We offer relocation assistance to new employees.

In this role, you will:

• Architect, build, and evolve large-scale ads ranking and recommendation systems using modern ML and AI techniques

• Design and productionize LLM- and transformer-inspired models that leverage sequential signals, long-horizon context, and sparse or delayed feedback.

• Develop model-driven decision logic and inference pipelines that operate under real-world constraints around performance, reliability, and privacy.

• Partner closely with Product, Design, and Research to define requirements and translate ambiguous product goals into scalable ML systems.

• Prototype, experiment, and rapidly iterate on new model architectures and training approaches to improve relevance, quality, and efficiency.

• Build services and infrastructure that support training, evaluation, online inference, and continuous optimization of ML models.

• Establish strong measurement, experimentation, and debugging practices to understand model behavior and system-level outcomes.

• Contribute to technical strategy and help shape the long-term evolution of OpenAI’s monetization and recommendation stack.

• Embed safety, fairness, and policy considerations directly into model design and system architecture from first principles.

You might thrive in this role if you:

• Have 6+ years of experience building and scaling ML-powered systems in production environments.

• Have worked on ranking, recommendation, ads, marketplaces, or large-scale ML inference systems.

• Are comfortable operating across the full stack — from model development to backend services and production deployment.

• Enjoy deeply technical 0→1 problem spaces where architecture, strategy, and implementation are still being invented.

• Have strong intuition for ML and system design tradeoffs, and can reason about long-term scalability and maintainability.

• Skills & Tags

  gorustawsaibackenddataproductdesign