OpenAI

Software Engineer, Monetization ML Infrastructure

OpenAI$130K — $180K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of professional software engineering experience in large-scale distributed systems or machine learning infrastructure.
  • Experience in building platforms for machine learning workflows, including data processing and model serving.
  • Familiarity with high-volume data pipelines and online systems infrastructure.
  • Proven ability to design systems with low-latency and strong operational visibility.
  • Comfortable navigating the entire machine learning lifecycle from data to deployment and monitoring.
  • Experience optimizing performance and reliability in production environments.

Responsibilities

  • Design and implement the ML infrastructure for OpenAI's monetization and advertising systems.
  • Develop large-scale data pipelines for processing various data inputs.
  • Create scalable platforms for model training to support a range of ML workloads.
  • Ensure safe and reliable transitions of models from experiments to production.
  • Enhance real-time inference infrastructure with strict performance criteria.
  • Establish experimentation frameworks for effective model assessments and strategies.
  • Optimize platform performance for efficiency, latency, and cost.

Benefits

  • Opportunity to work on foundational technology with a high business impact.
  • Collaboration with diverse teams, including machine learning engineers and data scientists.
  • Access to cutting-edge tools and technologies in the AI and machine learning fields.
  • Contribute to initiatives that leverage AI for solving global challenges.
Full Job Description
About the Role

We're looking for an experienced Software Engineer to help build the machine learning infrastructure that powers OpenAI's monetization and ads systems. In this foundational role, you'll design and develop the platform layer that enables teams to build, train, deploy, serve, monitor, and continuously improve machine learning models used across advertising and monetization products.

You'll work across the full ML lifecycle, from large-scale data pipelines and feature infrastructure to training systems, model serving, experimentation platforms, and monitoring frameworks. The systems you build will support high-throughput, low-latency advertising workloads while maintaining strict standards for reliability, privacy, security, and performance.

This role sits at the intersection of machine learning systems, distributed infrastructure, and monetization, offering the opportunity to shape the core platforms that help translate model innovation into measurable business impact.

In this role, you will:
  • Design and build the ML infrastructure that powers OpenAI's monetization and ads systems.
  • Develop large-scale data pipelines that process impressions, clicks, conversions, advertiser data, marketplace signals, and other inputs used to train and improve machine learning models.
  • Create scalable model training platforms that support ranking, conversion prediction, quality prediction, bidding, targeting, measurement, and optimization workloads.
  • Develop systems that safely and reliably move models from experimentation into production environments.
  • Build and improve real-time inference and serving infrastructure with strict requirements for latency, throughput, reliability, and availability.
  • Design experimentation frameworks that enable A/B testing, holdouts, model comparisons, ramping strategies, and measurement at scale.
  • Improve platform performance through optimization of training efficiency, inference latency, model throughput, infrastructure reliability, and cost effectiveness.
  • Collaborate closely with machine learning engineers, product engineers, data scientists, and monetization teams to accelerate the development and deployment of advertising systems.

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


At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

About OpenAI

OpenAI is an artificial intelligence research laboratory consisting of the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. The company was founded in 2015 by a group of technology leaders, including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, and John Schulman. OpenAI's mission is to develop and promote friendly AI for the betterment of humanity. The company has developed a number of cutting-edge AI technologies, including GPT-3, a language processing system that can generate human-like text. OpenAI has received funding from a number of high-profile investors, including LinkedIn co-founder Reid Hoffman and venture capitalist Peter Thiel.
Learn more about OpenAI
Size
100 employees
Industry
Founded
2015

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