Mohd Sadiq

AI Data Annotation Specialist with 2+ years of experience supporting Large Language Models (LLMs) and computer vision systems across multilingual projects in Arabic, Urdu, and English. Processed 10,500+ data points with 98%+ accuracy. Specialises in LLM evaluation, linguistic quality assessment, and prompt engineering. Demonstrated ability to reduce annotation errors, deliver structured feedback to engineering teams, and optimise data workflows for scalable AI deployment.

Associate Language Specialist at GlobalLogic (2025-05 – Present)

• Annotate and label AI datasets to improve training data quality, reducing inconsistencies by ~15%.
• Conduct validation checks maintaining 98% accuracy and reducing model errors by ~15%.
• Deliver structured feedback to engineering teams, improving response consistency and reducing hallucination errors.
• Manage multiple annotation pipelines, consistently delivering high-quality outputs within strict deadlines.

AI Trainer — Urdu at Outlier AI (2024-02 – 2024-08)

Concurrent contract alongside Scaled Solutions role

• Annotated and evaluated 500+ AI outputs in Urdu and English, reducing model errors by ~20%.
• Achieved 98% accuracy in multilingual evaluations, enhancing response fluency across both languages.
• Delivered structured feedback reports that improved output consistency for downstream model training.

Translator & Localizer at Scaled Solutions (2023-12 – 2024-11)

• Localised 10,000+ entries across Arabic, Urdu, and English, improving dataset usability for AI systems.
• Maintained 99% accuracy, ensuring high-quality training data for downstream LLMs.
• Optimised translation workflows, reducing processing time and enabling faster client deployment cycles.

M.A. in Arabic – Jawaharlal Nehru University, New Delhi (2022 – 2024)

B.A. Hons. in Arabic – Jawaharlal Nehru University, New Delhi (2019 – 2022)