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AI Counterfactual Explanation Generator Developer

Noah Kovacs

Full-time · Job · New_York

About the role

"Your loan was denied" tells the applicant nothing. "Your loan was denied because your debt-to-income ratio is 45%; if it were below 38%, you would have been approved" tells them exactly what to change. Counterfactual explanations answer the most natural human question about any decision: "What would I need to change to get a different outcome?" Generating good counterfactuals is harder than it sounds. The changes must be actionable ("increase your income" is possible; "be younger" is not), minimal (the closest possible world where the outcome changes), plausible (the resulting profile must look like a real person), and diverse (offering multiple paths to a different outcome). You'll build the counterfactual generation engine that satisfies all four criteria simultaneously. The explainability team is five engineers. You'll own the counterfactual module, working alongside the SHAP-based explanation team and the natural language explanation team. Each explanation approach serves a different audience; yours serves the people most affected by AI decisions.

Responsibilities

  • Build counterfactual explanation generation for classification and scoring models
  • Ensure counterfactuals are actionable, minimal, plausible, and diverse
  • Design constraint systems filtering non-actionable feature changes
  • Evaluate counterfactual quality against user comprehension studies
  • Support integration into client-facing decision explanation interfaces
  • Research new counterfactual methods as the field evolves

Requirements

  • 3+ years in ML with explainability or fairness focus
  • Understanding of counterfactual reasoning and constraint optimization
  • Strong Python and PyTorch skills for method implementation
  • Experience with user-facing explanation systems
  • Ability to bridge technical methods with real user needs

Benefits

  • Fully remote with flexible schedule
  • Health, dental, and vision insurance
  • $3,500 annual conference and learning budget
  • Stock options
  • Build explanations that empower people affected by AI decisions

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Categories

AI Product & Strategy AI & Machine Learning Engineers

Skills

python pytorch scikit-learn statistics docker

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI Product & Strategy AI & Machine Learning Engineers

Skills

python pytorch scikit-learn statistics docker fastapi

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