Human Data Operations Strategist

Manage and optimize data annotation workflows, ensuring high-quality data for AI models.

• •About us Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data.
• •Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production.
• •Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more.
• •We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator.
• •The role As a Human Data Operations Strategist, you will play a critical role in managing and optimising data annotation and machine learning workflows for our clients.
• •You will work closely with cross-functional teams, including clients, annotation specialists, and machine learning engineers, to ensure high-quality data is available for AI models.
• •What you'll do Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams Ensure the highest standards of data quality by designing and refining annotation processes, auditing results, and implementing feedback loops Act as a trusted advisor to clients, helping them design and implement the best data annotation workflow for their human annotation process Provide guidance and feedback to the annotation team, ensuring team members are equipped with the context and skills needed to perform high-quality work aligned with project requirements and best practices Work closely with product and engineering teams to drive improvements in AI training data processes, tools, and methodologies Who we're looking for A sharp, execution-oriented operator with a consulting or AI company pedigree
• •you bring structured thinking, strong project management instincts, and a bias for getting things done Analytically rigorous and comfortable with ambiguity
• •you break down complex operational challenges from first principles and build clear, actionable plans to solve them Technically fluent enough to get hands-on with data
• •whether that's querying a database, auditing annotation outputs, or automating a workflow in Python Passionate about AI and machine learning, with genuine curiosity about how data quality and operations underpin model performance A natural communicator who can translate fluidly between ML engineers and non-technical clients, keeping complex multi-stakeholder projects on track Entrepreneurial and collaborative