3 дня назад
BS Data Annotation Engineer (Computer Vision)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
BS Data Annotation Engineer (Computer Vision) (Python/ML data): Building and maintaining automation tooling and data pipelines for an image-recognition annotation platform with an accent on pre-labeling, dataset validation, and labeled-data quality control. Focus on integrating CVAT, supporting human-in-the-loop workflows, and translating model failure analysis into actionable annotation improvements.
Location: Ukraine; work type: Remote/Office
Company
Business Systems is a product company developing digital solutions for FMCG businesses, including an image-recognition platform used by brands and retailers.
What you will do
- Build and maintain Python scripts and tooling for pre-labeling, model-assisted annotation, format conversion, dataset validation, and progress tracking.
- Integrate annotation tools such as CVAT into the broader data pipeline.
- Support human-in-the-loop workflows where ML models generate preliminary labels for annotator review.
- Establish quality-control processes for labeled data, including double reviews, golden sets, spot checks, and inter-annotator agreement metrics.
- Track data-quality metrics, maintain annotation guidelines, and identify systematic issues before model training.
- Collaborate with ML Engineers, the annotation team lead, and the PM team to turn model failure analysis and recurring labeling issues into tooling and workflow improvements.
Requirements
- Working knowledge of Python and experience maintaining scripts for data processing, validation, and automation.
- Basic experience with computer-vision data, including bounding boxes, polygons, segmentation, or similar annotation formats.
- Basic understanding of ML model training and the impact of data quality on model performance.
- Experience with data annotation, labeling QA, or data-quality processes.
- Familiarity with annotation tools such as CVAT, or willingness to learn them quickly.
- Strong problem-solving skills, attention to detail, and a quality-first mindset.
Nice to have
- Familiarity with MLOps tools such as DVC, MLflow, or Label Studio ML backend.
- Experience with object-detection frameworks such as YOLO or Detectron2.
- Exposure to retail or FMCG domains, including planograms, SKUs, shelf monitoring, or category management.
Culture & Benefits
- Hands-on individual-contributor role focused on automation, data quality, and annotation-workflow improvement.
- Work on an image-recognition product used by FMCG brands and retailers.
- Collaborate with ML Engineers, annotation specialists, team leads, and product stakeholders.
- Remote/Office work format in Ukraine.
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