Haris Alam Zuberi

Key Skills

Software

Other

Labelbox

Label Studio

Mercor

Micro1

Mindrift

Toloka

Top Subject Matter

Mathematics Domain Expertise

Prompt Engineering

Mathematics AI Training

Top Data Types

Text

Document

Image

Top Task Types

Prompt Response Writing SFT

Entity Ner Classification

Question Answering

RLHF

Evaluation Rating

Classification

Freelancer Overview

Assistant Professor of Mathematics with academic, research, and AI-training experience. Brings extensive professional experience across higher education, mathematical research, technical writing, and quality-focused analytical work. Has served as Subject Matter Expert at Chegg India Pvt. Ltd. and Course Hero, and has also worked on AI training and evaluation projects with organizations such as Innodata, TELUS, and Turing. Core strengths include mathematics instruction, research mentoring, LaTeX, MATLAB, proof evaluation, data annotation, prompt engineering, and response quality assessment. Education includes a Ph.D. in Mathematics and M.Sc. in Mathematics. AI-training work includes text-based data, mathematical reasoning tasks, prompt-response writing, proof evaluation, and structured annotation workflows.

Labeling Experience

Mathematics Domain Expert

ImageQuestion Answering

Worked as a Mathematics Domain Expert at Innodata, contributing to high-quality multimodal question and answer (Q&A) generation for advanced AI training systems. The role involved designing, curating, and validating mathematically rigorous problems that integrate textual, visual, and analytical components, ensuring alignment with real-world reasoning and academic standards. Developed complex, graduate-level and research-oriented mathematical prompts across diverse areas such as algebra, calculus, geometry, and applied mathematics, often incorporating diagrams, graphs, and structured data for multimodal comprehension. Emphasized clarity, precision, and unambiguity while maintaining strict adherence to domain correctness and pedagogical depth. Additionally, evaluated AI-generated responses for logical consistency, solution completeness, and adherence to mathematical rigor, thereby enhancing model performance in handling sophisticated, verifiable reasoning tasks. The work significantly contributed to building robust datasets aimed at improving the reliability and interpretability of next-generation AI systems in mathematical problem-solving.

Worked as a Mathematics Domain Expert at Innodata, contributing to high-quality multimodal question and answer (Q&A) generation for advanced AI training systems. The role involved designing, curating, and validating mathematically rigorous problems that integrate textual, visual, and analytical components, ensuring alignment with real-world reasoning and academic standards. Developed complex, graduate-level and research-oriented mathematical prompts across diverse areas such as algebra, calculus, geometry, and applied mathematics, often incorporating diagrams, graphs, and structured data for multimodal comprehension. Emphasized clarity, precision, and unambiguity while maintaining strict adherence to domain correctness and pedagogical depth. Additionally, evaluated AI-generated responses for logical consistency, solution completeness, and adherence to mathematical rigor, thereby enhancing model performance in handling sophisticated, verifiable reasoning tasks. The work significantly contributed to building robust datasets aimed at improving the reliability and interpretability of next-generation AI systems in mathematical problem-solving.

2025 - Present

Data Annotator & Data Labeling and Reviewer

OtherTextEntity Ner Classification

As a Data Annotator and Reviewer at Soul AI (Deccan AI), I conducted detailed annotation of mathematical and technical datasets for AI training pipelines. My work involved high-precision entity recognition, formula interpretation, and contextual tagging to support machine learning model development. I reviewed, refined, and validated datasets to ensure consistency, accuracy, and adherence to demanding annotation guidelines on strict deadlines within a collaborative environment. • Annotated mathematical datasets for machine learning and AI model development. • Performed accuracy checks and context-based classification on symbolic expressions. • Reviewed and refined annotated data to meet quality assurance standards. • Enhanced dataset reliability for advanced mathematical AI solutions.

As a Data Annotator and Reviewer at Soul AI (Deccan AI), I conducted detailed annotation of mathematical and technical datasets for AI training pipelines. My work involved high-precision entity recognition, formula interpretation, and contextual tagging to support machine learning model development. I reviewed, refined, and validated datasets to ensure consistency, accuracy, and adherence to demanding annotation guidelines on strict deadlines within a collaborative environment. • Annotated mathematical datasets for machine learning and AI model development. • Performed accuracy checks and context-based classification on symbolic expressions. • Reviewed and refined annotated data to meet quality assurance standards. • Enhanced dataset reliability for advanced mathematical AI solutions.

2023 - 2024

AI Trainer / Reviewer and Prompt Engineer

TelusTextPrompt Response Writing SFT

As an AI Trainer and Prompt Engineer at Turing and Telus Digital International AI, I designed mathematically rigorous prompts and evaluated generative AI solutions for logical accuracy and pedagogical standards. My responsibilities included providing feedback to improve AI model reasoning and validating outputs for alignment with academic expectations. I ensured correctness in symbolic derivations, computation steps, and mathematical clarity while participating in remote, deadline-driven workflows. • Designed and refined prompts for advanced mathematical reasoning in AI. • Evaluated AI-generated responses for logical and pedagogical consistency. • Provided structured feedback to optimize AI reasoning and performance. • Validated outputs in specialized mathematics-focused AI training projects.

As an AI Trainer and Prompt Engineer at Turing and Telus Digital International AI, I designed mathematically rigorous prompts and evaluated generative AI solutions for logical accuracy and pedagogical standards. My responsibilities included providing feedback to improve AI model reasoning and validating outputs for alignment with academic expectations. I ensured correctness in symbolic derivations, computation steps, and mathematical clarity while participating in remote, deadline-driven workflows. • Designed and refined prompts for advanced mathematical reasoning in AI. • Evaluated AI-generated responses for logical and pedagogical consistency. • Provided structured feedback to optimize AI reasoning and performance. • Validated outputs in specialized mathematics-focused AI training projects.

2023 - 2024

Education

Work History