Nitin Y.

Key Skills

Software

Data Annotation Tech

Top Subject Matter

Physics and Mathematics (Quantum Mechanics, Advanced Linear Algebr) Classical mechanics

Data Validation, Fraud Pattern Recognition & Numerical Analysis"

E-commerce & Technical Content: Taxonomy, Data Categorization & Quality Assurance

Top Data Types

Text

3D Sensor

Computer Code Programming

Top Task Types

RLHF

Fine-tuning

Freelancer Overview

Subject Matter Expert | AI training and alignment (Physics education dataset creation and verification). Brings 20+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose. Education includes Bachelor of Science, Banaras Hindu University. AI-training focus includes data types such as Text and labeling workflows including Fine-tuning.

Labeling Experience

Subject Matter Expert | AI training and alignment (Physics education dataset creation and verification)

Don't discloseTextFine-tuning

• Served as a Subject Matter Expert for AI training and alignment using Physics domain knowledge to produce accurate training materials. • Developed solution content and verified conceptual correctness to improve quality for LLM fine-tuning. • Curated and debugged physics training datasets to support logical rigor and reduce hallucinations in technical domains. • Ensured subject-matter accuracy for educational/technical alignment data. • Applied structured mental frameworks to simplify and standardize complex physics problems for dataset consistency. • Performed dataset quality checks and precision-focused review for fine-tuning readiness. • Contributed to technical writing and fact-checking aligned with AI tutoring/training objectives.

2026 - Present

Subject Matter Expert | AI training and alignment (Self-employed)

Don't discloseTextRLHF

Served as a Subject Matter Expert focused on AI training and alignment, leveraging domain knowledge to improve model behavior and responses. Contributed to refining training inputs by ensuring technical accuracy and consistency with physics/quantitative reasoning expectations. Supported alignment-related iteration cycles typical of AI tutoring and training workflows for educational content. • Validate and review AI responses against physics and math concepts • Provide training guidance to improve correctness, clarity, and reasoning quality • Support prompt/response improvement aligned with educational objectives • Iterate feedback loops to enhance model alignment and reliability

2026 - Present

Education

Work History