Direct message the job poster from Averroes.ai
Tareq Aljaber
Tareq Aljaber
Founder & CEO @ Averroes.ai - Make Production Lines See Better™
About VisionRepo
VisionRepo (https://visionrepo.ai/visionrepo) is an AI data management and auto-labeling platform designed to help teams build high-quality computer vision datasets faster. Users label a small sample, build a custom auto-labeling engine, and let AI handle the rest. VisionRepo supports classification, detection, and segmentation workflows and is used across industrial and enterprise CV use cases.
We are looking for a hands-on Computer Vision Engineer who can work directly on real datasets, understand user workflows, and help customers and internal teams get maximum value from the VisionRepo platform.
Role Overview
This role is focused on applied computer vision, not academic research. You will work hands-on with VisionRepo to build and evaluate auto-labeling engines, improve model performance, and strengthen the underlying backbone models used by the platform.
Responsibilities
Use VisionRepo to build, test, and refine auto-labeling engines for classification, detection, and segmentation
Label small seed datasets and validate AI-generated annotations at scale
Analyze edge cases, failure modes, and data quality issues
Work closely with product and engineering teams to improve workflows and usability
Support internal demos, PoCs, and customer evaluations using VisionRepo
Provide structured feedback on platform performance, limitations, and feature gaps
Help define best practices for dataset creation, validation, and iteration using VisionRepo
Requirements
Strong understanding of computer vision fundamentals (classification, detection, segmentation)
Hands-on experience with CV datasets and annotation workflows
Familiarity with deep learning concepts and model evaluation (accuracy, precision/recall, confusion matrices, etc.)
Practical mindset: able to work with imperfect data and iterate quickly
Comfortable learning and adopting new tools and platforms
Clear communication skills for explaining results and trade-offs
Nice to Have
Experience with industrial or real-world CV use cases
Experience evaluating or improving data labeling pipelines
Familiarity with active learning or human-in-the-loop systems
[IMPORTANT] Platform Familiarity Requirement
As part of the application process, candidates will be asked to:
Explore the VisionRepo platform (https://visionrepo.ai/visionrepo)
Describe how they would use it to build an auto-labeling engine for a real computer vision problem
Share concrete feedback on how the platform can be leveraged or improved
This role requires curiosity, hands-on usage, and a willingness to learn by doing.
What We Offer
Opportunity to work on a production CV platform used by real customers
Exposure to multiple industries and datasets
Direct impact on product direction and user experience
Fast-moving, no-bureaucracy environment
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Seniority level
Entry level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Semiconductor Manufacturing