Machine Learning Engineer, Core Experimentation

OpenAI
Bellevue, Seattle
Workplace: HybridFull timeUSD 437,000 - 485,000 annuallyFunction: Data Science & Machine LearningSkills: ["Technical leadership","Collaboration","Product thinking","Problem-solving","Communication"]

Lead end-to-end ML-powered experimentation and insights capabilities, building systems that learn from privacy-protected product and experiment data to generate traceable, calibrated, and safe evidence-backed predictions. Design uncertainty-aware live experimentation workflows, backtest against historical outcomes, and create datasets, retrieval/feature pipelines, and evaluation/monitoring (calibration, drift, abstention). Turn models into durable product/API and agent workflows used by teams across OpenAI.

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FursaFursa
OpenAI
OpenAI
13 hours ago

Machine Learning Engineer, Core Experimentation

āœ“ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 13 hours agoStatus: Live

Job Summary

Lead end-to-end ML-powered experimentation and insights capabilities, building systems that learn from privacy-protected product and experiment data to generate traceable, calibrated, and safe evidence-backed predictions. Design uncertainty-aware live experimentation workflows, backtest against historical outcomes, and create datasets, retrieval/feature pipelines, and evaluation/monitoring (calibration, drift, abstention). Turn models into durable product/API and agent workflows used by teams across OpenAI.
Location: Bellevue, Seattle
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • ā€¢Set and execute the technical roadmap for Generative Insights and Predictive Experimentation from prototype to production adoption.
  • ā€¢Build cross-experiment learning systems that retrieve and synthesize historical results, detect effects/segmentation patterns, and generate evidence-backed hypotheses.
  • ā€¢Develop predictive models and simulation workflows to estimate impact, affected segments, regression risk, and uncertainty before live experiments.
  • ā€¢Create high-quality datasets and feature/retrieval pipelines with strong lineage, freshness, privacy, and data-quality controls.
  • ā€¢Establish rigorous evaluation via offline benchmarks, backtests, calibration, drift monitoring, and explicit failure/abstention behavior.

Pay and Benefits

Salary: USD 437,000 - 485,000 annually
Equity and Bonus:Equity

Key Requirements

  • ā€¢Hands-on experience across the ML lifecycle, including dataset design, training/adaptation, evaluation, deployment, monitoring, and iteration.
  • ā€¢Strong foundation in machine learning, statistics, and computer science, with the ability to build reliable production systems.
  • ā€¢Experience leading 0-to-1 ML products where success is measured by improved real-world decisions, not only offline metrics.
  • ā€¢Background in experimentation and statistical reasoning, including understanding why predictive accuracy differs from causal validity.
  • ā€¢Ability to treat calibration, uncertainty, provenance, privacy, and human review as product requirements.
Skills:Technical leadershipCollaborationProduct thinkingProblem-solvingCommunication
Tech Stack:PythonLLMRetrievalAPIs

Company Brief

OpenAI
Develops and deploys advanced generative AI models (including ChatGPT and DALLĀ·E) and AI infrastructure, providing APIs and consumer products to accelerate safe AGI for broad benefit.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Hectocorn (USD 100B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2015
Glassdoor
Glassdoor: 4.4
WebsiteLinkedInGlassdoor