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Software Engineer, Monetization ML Infrastructure

OpenAI· Applied AI
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Hybrid (San Francisco)Full-timePosted 4mo ago

About the role

Software Engineer to design and build the machine learning infrastructure powering OpenAI’s monetization and ads systems, covering data pipelines, training platforms, model deployment, real-time serving, experimentation, and monitoring in a hybrid San Francisco role.

Responsibilities

  • 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.

Qualifications

  • 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.

Skills

Required:Large-scale distributed systemsML infrastructure platformsData pipelinesModel training and servingExperimentation frameworks

Benefits

  • Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
  • Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
  • 401(k) retirement plan with employer match
  • Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
  • Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
  • 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time
  • Mental health and wellness support
  • Employer-paid basic life and disability coverage
  • Annual learning and development stipend
  • Daily meals in our offices, and meal delivery credits as eligible
  • Relocation support for eligible employees
  • Additional taxable fringe benefits, such as charitable donation matching and wellness stipends
Last updated Sep 3, 2026. Interested? Apply on the company site.

About OpenAI

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Company profileWebsite

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