AI Data Operations Lead - Human-in-the-Loop Workflows

Encord; Greater London; On-site; GBP 70,000 - 120,000; Full time

Benefits offered by this job

Competitive salary & equity

4 days per week culture

Flexible PTO

Learning & development budget

Health, dental, and vision

Travel across US, London, Europe

Bi-annual offsites & social events

Job summary

Encord is seeking a Human Data Operations Strategist to manage data annotation and ML workflows for clients. You’ll partner with clients, annotation specialists, and ML engineers to ensure high-quality data for AI models, translating complex requirements into actionable processes.

You will lead multi-stakeholder projects, design robust annotation pipelines, and mentor teams to align with project goals and best practices.

Qualifications

• 3-7 years of professional experience in strategy consulting or operations/data roles at leading AI or technology companies.
• Proven ability to own complex, multi-stakeholder data workflows end-to-end—from scoping to execution and QA.
• Proficiency in Python or SQL to query data, automate workflows, or audit annotation outputs.
• Experience designing data operations processes with emphasis on quality, consistency, and scalability.
• Ability to engage with both ML engineers and non-technical clients to translate requirements.

Responsibilities

• Oversee data annotation projects, translating AI/ML requirements into clear workflows for annotation teams.
• Improve data quality by designing/analyzing annotation processes and implementing feedback loops.
• Advise clients on best data annotation workflows for their needs.
• Guide annotation teams with context and skills to meet project standards.
• Collaborate with product and engineering to enhance AI training data processes and tooling.

Skills

Project management

Data annotation

Python

SQL

Quality assurance

Client communication

Job description

Encord is seeking a Human Data Operations Strategist to manage data annotation and ML workflows for clients. You’ll partner with clients, annotation specialists, and ML engineers to ensure high-quality data for AI models, translating complex requirements into actionable processes.

You will lead multi-stakeholder projects, design robust annotation pipelines, and mentor teams to align with project goals and best practices.