Job Description

Job Title: Data Operations Manager, Human Data Operations

Company: Netflix

Years of Experience: 5+ years in human data operations, AI/ML evaluation, or operational leadership

Location: Remote

Role Type: Full-Time

Salary: $70,000 – $370,000 (annual, flexible between salary and stock options)

Eligibility:

• 5+ years of experience in human data operations, AI/ML evaluation, or related operational leadership roles.
• Proven experience managing and scaling teams and operations in fast-paced, ambiguous environments.
• Experience managing budgets, vendor sourcing, and cross-functional partnerships.

Role Overview

The Human Data Operations Manager will build and scale a new function that connects human insight to AI/ML development. You’ll lead a team managing human data annotation and evaluation workflows, establish operational standards, optimize cost and quality, and collaborate closely with Product, Research, Engineering, and Data Science teams. This role balances hands-on execution with strategic advising, driving scalable, high-quality human-in-the-loop (HITL) data operations to support Netflix’s AI initiatives.

Key Responsibilities

• Lead, coach, and develop program/project managers and human raters, fostering high-performing teams.
• Design, implement, and scale human data workflows for ML/GenAI use cases.
• Manage budgets, vendor sourcing, and external partnerships for annotation work.
• Prioritize and make trade-offs across multiple AI evaluation initiatives.
• Collaborate cross-functionally to align human data operations with strategic priorities.
• Pilot automation and tooling to improve scalability, efficiency, and quality.
• Define best practices, governance, and documentation to ensure repeatability and consistency.
• Measure and optimize the impact of human data on AI product and model development.

Skills and Qualifications

• 5+ years in human data operations, ML evaluation, or AI/ML operational leadership.
• Proven success managing and scaling teams in fast-paced environments.
• Strong experience in budget management, vendor sourcing, and external partnerships.
• Knowledge of evaluation frameworks, scoring rubrics, and LLM/GenAI outputs.
• Cross-functional collaboration, influencing senior stakeholders, and strategic advising.
• Operational rigor, process design, and scaling workflows.
• Comfortable navigating ambiguity, leading change, and improving efficiency.
• Excellent communication, data-driven decision making, and responsible AI knowledge.