软件工程师，货币化机器学习基础设施
Software Engineer, Monetization ML Infrastructure
关于团队
Monetization 团队是一个跨职能小组，成员来自工程、产品、研究和设计领域，致力于构建基础系统，以负责任的方式帮助 OpenAI 扩展智能访问。我们的使命是开发以用户为中心、保护隐私的货币化产品，包括下一代广告体验，从而增强用户信任，释放经济机会，并支持 OpenAI 的长期创新。
货币化在使 OpenAI 能够持续推动 AI 能力边界的同时，确保通用人工智能（AGI）的好处得到广泛分享方面发挥着关键作用。我们认为货币化必须与用户价值保持一致，坚持严格的隐私和安全标准，并维持开发者和企业健康的生态系统。
该团队在一个全新的环境中运作，通过原型设计、实验和迭代部署快速推进。我们与产品、设计和研究团队紧密合作，将研究突破转化为全球规模的现实系统。
关于职位
我们正在寻找一位经验丰富的软件工程师，帮助构建支撑 OpenAI 货币化和广告系统的机器学习基础设施。在这个基础性角色中，您将设计和开发平台层，使各团队能够构建、训练、部署、服务、监控并持续改进用于广告和货币化产品的机器学习模型。
您将参与整个机器学习生命周期，从大规模数据管道和特征基础设施到训练系统、模型服务、实验平台和监控框架。您构建的系统将支持高吞吐量、低延迟的广告工作负载，同时保持对可靠性、隐私、安全性和性能的严格标准。
这个职位位于机器学习系统、分布式基础设施和货币化交叉点，提供塑造核心平台的机会，这些平台有助于将模型创新转化为可衡量的业务影响。
在此职位上，您将：
- 设计和构建支撑 OpenAI 货币化和广告系统的机器学习基础设施。
- 开发大规模数据管道，处理展示、点击、转化、广告商数据、市场信号和其他用于训练和改进机器学习模型的输入。
- 创建可扩展的模型训练平台，支持排名、转化预测、质量预测、竞价、定向、测量和运营。
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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 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.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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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.