Encord
GrowthData curation and active learning platform for computer vision AI. FDEs embed with ML teams to build annotation pipelines, set up active learning loops that prioritize the most valuable unlabeled data, and improve model performance using production data feedback.
Signals from job descriptions
Patterns mined from Encord's open FDE postings
- 01
Active learning loop configuration appears in all FDE roles. FDEs are improving models iteratively using production data, not just setting up static annotation pipelines.
- 02
Healthcare is the fastest-growing vertical based on recent job posting frequency, reflecting demand for computer vision in clinical imaging.
- 03
PyTorch is listed as required in Encord FDE roles, unusual for a data tooling company. Suggesting FDEs debug and validate model behavior, not just data pipelines.
Tech stack
Inferred from job descriptions
Languages
AI / ML
Cloud & infra
Tools & integrations
Sectors
Hiring regions
- United States
- UK & Europe
Seniority mix
- Mid-level / unspecified5
Put an embedded AI team on your roadmap
Forward-deployed engineers to deploy, AI-native engineers to build, and on-demand QA pods to validate, embedded with your team, starting the same day.