Data Annotation & AI Support Associate

Job Title: Data Annotation & AI Support Associate

About the Role

We are looking for a detail-oriented Data Annotation & AI Support Associate to help our AI/ML team prepare high-quality datasets for various machine learning projects. The role involves working with images, videos, spreadsheets, and basic Python scripts to support both data labelling and data quality verification. You will review datasets, check Excel sheets for inconsistencies or anomalies, and ensure that all data is clean, accurate, and ready for model training.

Key Responsibilities

1. Image & Video Annotation

Draw bounding boxes, segmentation polygons, and keypoints. Label objects consistently following internal annotation guidelines. Review and correct previously annotated samples. Watch raw videos to identify usable clips, remove bad samples, and flag anomalies or mislabelled frames.

2. Data Cleaning & Quality Control

Clean image and video datasets by removing duplicates, corrupted files, and poor-quality samples. Validate dataset folder structures, filenames, metadata, and formats. Maintain organized dataset versions (raw, processed, clean). Review footage and determine if clips are valid, incomplete, or low-quality.

3. Excel & Spreadsheet Analysis

Work with Excel/Google Sheets to: Sort, filter, and inspect data. Identify anomalies, inconsistencies, missing values, and outliers. Compute basic statistics such as mean, median, and mode. Prepare small summary reports for the AI team.

4. Python Utility Tasks (Good to Have)

Run simple preprocessing or conversion scripts. Write basic Python code to automate repetitive tasks (renaming, filtering, merging). Use Jupyter notebooks or CLI tools for basic data exploration.

Requirements

Experience with annotation tools (CVAT, Label Studio, Roboflow, VGG Annotator, etc.)

Strong attention to detail, especially during repetitive data review tasks. Comfort working with Excel/Google Sheets and large datasets.

Basic understanding of Python, NumPy, or Pandas (preferred). Ability to work with large files, cloud storage, and structured folders.

Nice to Have

Prior experience with AI/ML data preparation or annotation.

Understanding of object detection formats (YOLO, COCO, Pascal VOC).

Familiarity with dataset validation and quality-check techniques. Exposure to Git, Linux, or Jupyter Notebooks.

Soft Skills

Strong communication and ability to collaborate with engineers.

Reliable, consistent, and responsible in task execution.

Ownership mindset with emphasis on delivering high quality work.