Director of AI Evaluation

Career Guide

A Director of AI Evaluation leads how an organization measures, tests, and improves the quality, safety, and real-world performance of AI systems. The role builds evaluation strategy, defines success metrics, and ensures models behave reliably across diverse users, languages, and scenarios.

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Key Responsibilities

Set the evaluation vision and roadmap for AI products
Define quality standards and acceptance criteria for model releases
Design evaluation frameworks for accuracy, reliability, and safety
Create benchmark test suites and maintain them over time
Oversee human review programs and labeling quality
Partner with Product to align evaluation goals with user outcomes
Partner with Engineering to integrate evaluation into development workflows
Partner with Legal and Policy to assess compliance and risk
Lead incident reviews for AI failures and quality regressions
Build and manage a team of evaluation engineers and analysts
Report model performance to executives with clear, decision-ready insights
Manage vendor relationships for data collection and human review services

Top Skills for Success

Evaluation Strategy

Metric Definition

Benchmark Design

Test Coverage Planning

Human Review Program Design

Data Quality Management

Experiment Design

Error Analysis

Prompt Testing

Model Behavior Analysis

Risk Assessment

AI Safety Principles

Privacy Awareness

Governance Practices

Technical Communication

Stakeholder Management

People Leadership

Program Management

Career Progression

Can Lead To

Head of AI Quality

Head of AI Safety

Director of Machine Learning Platform

VP of AI Product

Chief AI Officer

Transition Opportunities

Product Leadership

Trust and Safety Leadership

Risk and Compliance Leadership

Data Science Leadership

Machine Learning Engineering Leadership

Common Skill Gaps

Often Missing Skills

Production Evaluation DesignHuman Review OperationsSafety Evaluation MethodsRelease Readiness ProcessesExecutive ReportingCross Functional Governance

Development SuggestionsBuild experience owning model launch decisions, create repeatable evaluation scorecards, and run a full evaluation lifecycle from test design to release sign-off. Practice translating model behavior into business impact, user risk, and clear tradeoffs for leadership.

Market Intelligence Report

Director of AI Evaluation is part of the Machine Learning category.Explore our market intelligence report to see how AI and hiring demand are shifting for these roles.

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Salary & Demand

Median Salary Range

Entry Level$190,000 to $250,000

Mid Level$250,000 to $330,000

Senior Level$330,000 to $450,000

Growth Trend

Strong growth as companies ship more AI features and face higher expectations for quality, safety, and accountability. Demand is highest in organizations deploying customer-facing AI at scale.

Companies Hiring

Major Employers

OpenAIGoogleMicrosoftAmazonMetaAppleNVIDIAAnthropicCohereIBMSalesforceDatabricks

Industry Sectors

Consumer TechnologyEnterprise SoftwareCloud ServicesFinancial ServicesHealthcare TechnologyEcommerceMedia and AdvertisingCustomer Support PlatformsCybersecurityAutonomous Systems

Recommended Next Steps

Draft an evaluation charter that defines what good looks like for your organization

Create a core metric set that ties model quality to user outcomes

Inventory current test coverage and identify high-risk gaps

Build a benchmark suite that reflects real customer tasks

Establish a human review workflow with clear guidelines and audit checks

Implement automated evaluation in the model release pipeline

Set up a monthly quality review with Product, Engineering, and Policy

Publish a one-page executive dashboard for model readiness

Run a pilot safety evaluation on one high-impact use case

Hire for key roles such as evaluation engineering and human review operations