Human Data Solutions Engineer

Requirements

• 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.
• 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.
• You are the expert who takes a prospect from first demo to a working proof of concept — not just by showing the platform, but by actually delivering a small-scale, high-quality annotation sample that demonstrates what best-in-class data operations looks like in practice.
• With a strong focus on robotics and autonomous driving, you'll be working with some of the most technically complex and data-intensive AI use cases in the industry.
• What you’ll do - Partner with Account Executives to lead the technical and operational strategy for complex enterprise sales cycles, co-owning the path to a successful proof of concept - Lead deep technical discovery sessions with ML Engineers, MLOps leaders, and non-technical stakeholders to understand data
• requirements and design the right annotation workflow - Manage end-to-end delivery of small-scale annotation POCs — translating complex AI
• requirements - 1-3 years of professional experience, ideally spanning strategy consulting, AI/technology operations, or customer-facing technical roles (Solutions Engineering, Technical Account Management, or similar) - Proven ability to own complex, multi-stakeholder workflows end-to-end — from scoping and planning through execution, quality assurance, and client communication - Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs -
• Experience designing or optimising data operations processes with a strong eye for quality, consistency, and scalability — ideally involving human-in-the-loop or structured labelling workflows - Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients - Hands-on
• experience with at least one major cloud platform (GCP, AWS, or Azure), including data storage and ML workflow patterns - Bonus: hands-on
• experience with computer vision, LiDAR, robotics sensor data, or autonomous driving datasets; prior exposure to data annotation platforms or quality management frameworks;
• experience in a customer-facing technical role at an AI company Why Encord - Competitive salary, commission, and equity in a high-growth startup - Strong in-person culture — most of the team works from our London office 3+ 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