CordTechnologies - Encord - Human Data Operations Strategist
Requirements
• 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 — you thrive in fast-paced environments and take ownership without waiting to be told what to do • 3–7 years of professional experience, with a strong preference for backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies • Proven ability to own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and iteration • Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs; broader familiarity with relational databases or data annotation tooling equally valued • Experience designing or optimising data operations processes with a strong eye for quality, consistency, and scalability — ideally in a context involving human-in-the-loop workflows or structured labelling tasks • Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients, translating requirements clearly in both directions • Bonus: hands-on experience with computer vision, generative AI, or multimodal data workflows; prior exposure to data annotation platforms or quality management frameworks; experience coaching or managing operational teams
Responsibilities
• 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
Benefits
• Competitive salary, commission, and equity in a high-growth start-up • Strong in-person culture — most of the team works from our London office 4+ days/week • 25 days annual leave + UK public holidays • Annual learning & development budget • Travel for customer visits, events, and conferences across the UK and Europe • Company lunches twice a week • Monthly socials & bi-annual team offsites
Apply in one click
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT