Responsibilities:

Annotation & Labeling: Apply accurate tags, bounding boxes, or classifications to text, image, audio, or video data according to project guidelines.
Pipeline Automation: Develop and maintain Python scripts/APIs for data ingestion, pre-processing, and integration into machine learning pipelines.
Quality Assurance (QA): Build automated tools for QA sampling, label consistency checks, and identifying data set anomalies.
Guideline Refinement: Collaborate directly with ML Engineers and Data Scientists to clarify ambiguities in data and update annotation ontologies.
Evaluation: Review AI-generated outputs for accuracy, bias, and performance metrics, creating clear experiment tracking logs.
Contribute to CI/CD pipelines and cloud infrastructure (AWS/GFCP/Azure).

Requirements:

3+ years of professional Python development experience.
Proficiency in Python (e.g., pandas, NumPy, scikit-learn, or standard APIs).
Foundational understanding of machine learning workflows, NLP, computer vision, or LLM fine-tuning.
Strong problem-solving ability, exceptional attention to detail, and the ability to apply multi-page annotation rules consistently.
Ability to collaborate with technical teams and provide constructive feedback on dataset quality.

Preferred Requirements: