About the role
Work with image and video datasets, annotation systems, model training, evaluation and applied computer-vision pipelines under technical supervision. You will be directly involved in production AI development — not academic exercises.
Responsibilities
- Prepare and curate image/video datasets for model training
- Review and validate annotations for quality assurance
- Run training experiments and document configurations
- Evaluate model performance with structured metrics
- Perform error analysis and categorise failure modes
- Conduct computer-vision literature reviews
- Build Python tooling for data pipelines
- Test model deployments in staging environments
- Document experiments, results and technical decisions
Expected foundation
We expect you to have working knowledge of:
Preferred exposure
Bonus if you have touched any of these:
What you will learn
- How production CV systems differ from notebook experiments
- Structured evaluation methodology beyond mAP
- Dataset engineering and annotation quality control
- Edge deployment and inference optimisation
- Working within a coordinated AI engineering team
How to apply
Send your resume (or LinkedIn), a link to any relevant work (GitHub, Kaggle, papers), and a brief statement on what technical problem interests you most.