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Software Development

Software Engineer, Monetization ML Infrastructure

OpenAI · San Francisco · full-time · Hybrid

Software Developmentfull-timeHybridSan Francisco$347K – $445K
Applied AIApplied AI Engineering
RemoteJobs editorial overview

Strategic Overview

Software Engineer, Monetization ML Infrastructure at OpenAI is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.

The published role emphasizes work such as 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…

The role is listed for San Francisco with hybrid working arrangement, giving candidates the practical context needed to assess fit before applying. Relevant signals in the listing include Applied AI, Applied AI Engineering.

Job seeker snapshot

Key information at a glance

Role focusSoftware Development
LocationSan Francisco
WorkplaceHybrid
Employmentfull-time
Experience7+ years
Salary$347K – $445K
PostedJun 1, 2026
Last seenOct 25, 2026
Role context

About This Role

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…

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.

What the role delivers

Key Responsibilities & Objectives

  • 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.
Candidate blueprint

Required Qualifications & Candidate Blueprint

  • Have worked with high-volume data pipelines and infrastructure handling large-scale online systems.
Compensation & benefits

Salary & Benefits

Published compensation: $347K – $445K

Live market comparison

Salary Benchmark

This role’s published compensation is compared with current employer-disclosed salary ranges for the same role in the same currency.

This job$347K – $445K
Current market range$86 – $625,000
Comparable jobs497

Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.

Employer-provided source content

Full Job Description

The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.

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.

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.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

OpenAI Global Applicant Privacy Policy

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.

RemoteJobs original analysis

Editor’s Market Perspective (Our Custom Analysis)

Why This Position Matters

This dev opening is a useful opportunity for candidates whose experience matches Applied AI, Applied AI Engineering. Its strongest career signal is the scope of the work itself — particularly Design and build the ML infrastructure that powers OpenAI’s monetization and ads systems. — rather than a generic title alone.

Resume & Application Strategy

For the application, mirror the employer's language where it truthfully matches your background: foreground Applied AI, Applied AI Engineering, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.

Source transparencyashby

We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.