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OpenAI
OpenAI

Software Engineer, Monetization ML Infrastructure

RemoteUnited States only
Published
Role
AI / ML
Experience
Senior
Employment
Full-time
$293k–$441k/yr
Check eligibility

Open to US only. Set where you work from to check your eligibility.

No BS summary

Experienced software engineer with 7+ years building large-scale distributed systems or ML infrastructure. Must have ML workflow platform experience, high-volume data pipelines, and low-latency production systems. US-based remote role focused on monetization and ads ML infrastructure.

Core skills

ML infrastructureData pipelinesModel serving

What you'll do

  • Design and build ML infrastructure for OpenAI’s monetization and ads systems
  • Develop large-scale data pipelines for impressions, clicks, conversions, advertiser data, marketplace signals, and other ML inputs
  • Create scalable model training platforms for ranking, conversion prediction, quality prediction, bidding, targeting, measurement, and optimization workloads
  • Develop systems to move models from experimentation into production safely and reliably
  • Build and improve real-time inference and serving infrastructure with strict latency, throughput, reliability, and availability requirements
  • Design experimentation frameworks for A/B testing, holdouts, model comparisons, ramping strategies, and measurement at scale
  • Optimize training efficiency, inference latency, model throughput, infrastructure reliability, and cost effectiveness
  • Collaborate with machine learning engineers, product engineers, data scientists, and monetization teams

What they require

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

Benefits

  • Offers equity
  • Reasonable accommodations for applicants with disabilities

American artificial intelligence research organization

🇺🇸 United StatesAIEnterpriseopenai.com
$293k–$441k/yr