Azure Data Engineer. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution.
Education includes Bachelor of Technology, Shivaji University (2024).
• Reviewed and evaluated AI-generated Python code for correctness, efficiency,
and adherence to best practices including proper use of functions, loops,
list comprehensions, exception handling, and OOP principles.
• Annotated SQL query outputs generated by AI models, assessing correctness
of SELECT, JOIN, GROUP BY, subquery, and window function logic against
given problem statements and expected results.
• Performed code debugging tasks by identifying logical errors, syntax issues,
and edge-case failures in Python scripts submitted by AI systems, and
provided corrected reference solutions with explanations.
• Rated and ranked multiple AI-generated code solutions based on criteria
such as time complexity, readability, correctness, and Pythonic style to
support RLHF (Reinforcement Learning from Human Feedback) pipelines.
• Evaluated Python data manipulation tasks involving pandas, NumPy, and
standard library modules — checking output accuracy, data type handling,
and edge case coverage.
• Annotated SQL tasks across difficulty levels including basic filtering,
multi-table joins, aggregations, CTEs (Common Table Expressions), and
correlated subqueries for enterprise-grade AI model training datasets.
• Provided detailed written rationales and step-by-step explanations for
each code annotation decision, improving model understanding of reasoning
behind correct and incorrect code patterns.
• Maintained a high performer rating on the Toloka platform with consistent
accuracy scores above 95%, completing 300+ coding annotation tasks across
Python and SQL categories.
• Followed strict annotation guidelines and taxonomy frameworks to ensure
inter-annotator agreement and label consistency across large-scale
coding datasets used in AI fine-tuning.
• Contributed to NLP-adjacent tasks such as labeling code comments,
docstrings, and technical documentation for clarity, completeness,
and grammatical correctness.
• Reviewed and evaluated AI-generated Python code for correctness, efficiency,
and adherence to best practices including proper use of functions, loops,
list comprehensions, exception handling, and OOP principles.
• Annotated SQL query outputs generated by AI models, assessing correctness
of SELECT, JOIN, GROUP BY, subquery, and window function logic against
given problem statements and expected results.
• Performed code debugging tasks by identifying logical errors, syntax issues,
and edge-case failures in Python scripts submitted by AI systems, and
provided corrected reference solutions with explanations.
• Rated and ranked multiple AI-generated code solutions based on criteria
such as time complexity, readability, correctness, and Pythonic style to
support RLHF (Reinforcement Learning from Human Feedback) pipelines.
• Evaluated Python data manipulation tasks involving pandas, NumPy, and
standard library modules — checking output accuracy, data type handling,
and edge case coverage.
• Annotated SQL tasks across difficulty levels including basic filtering,
multi-table joins, aggregations, CTEs (Common Table Expressions), and
correlated subqueries for enterprise-grade AI model training datasets.
• Provided detailed written rationales and step-by-step explanations for
each code annotation decision, improving model understanding of reasoning
behind correct and incorrect code patterns.
• Maintained a high performer rating on the Toloka platform with consistent
accuracy scores above 95%, completing 300+ coding annotation tasks across
Python and SQL categories.
• Followed strict annotation guidelines and taxonomy frameworks to ensure
inter-annotator agreement and label consistency across large-scale
coding datasets used in AI fine-tuning.
• Contributed to NLP-adjacent tasks such as labeling code comments,
docstrings, and technical documentation for clarity, completeness,
and grammatical correctness.
2025 - 2026
Data Annotator (Contract)
TextText Summarization
Data Annotator (Contract) | RWS Group Remote | Mar 2024 – Present
• Annotated multilingual text datasets for NLP tasks including sentiment analysis, named entity recognition
(NER), and intent classification.
• Labeled conversation transcripts and customer support dialogues to train AI chatbots and virtual assistants.
• Reviewed and quality-checked peer annotations to maintain inter-annotator agreement above 90%.
• Worked with structured annotation tools and followed detailed style guides and taxonomy frameworks for
enterprise clients.
• Delivered 1,000+ annotations per sprint while maintaining high accuracy under tight deadlines.
Data Annotator (Contract) | RWS Group Remote | Mar 2024 – Present
• Annotated multilingual text datasets for NLP tasks including sentiment analysis, named entity recognition
(NER), and intent classification.
• Labeled conversation transcripts and customer support dialogues to train AI chatbots and virtual assistants.
• Reviewed and quality-checked peer annotations to maintain inter-annotator agreement above 90%.
• Worked with structured annotation tools and followed detailed style guides and taxonomy frameworks for
enterprise clients.
• Delivered 1,000+ annotations per sprint while maintaining high accuracy under tight deadlines.
2024 - 2025
AI Training Contributor
ImageRLHF
AI Training Contributor (Freelance) | Outlier AI Remote |
• Completed RLHF (Reinforcement Learning from Human Feedback) tasks by ranking and rating AIgenerated outputs to improve large language model quality.
• Annotated and evaluated responses for factual accuracy, coherence, tone, and instruction-following across
multiple prompt categories.
• Performed code review and debugging annotation tasks for Python and SQL outputs generated by AI
models.
• Maintained 95%+ quality score across 500+ completed tasks through strict adherence to platform
guidelines.
• Provided detailed written rationales for model feedback, contributing to fine-tuning pipelines for generative
AI Training Contributor (Freelance) | Outlier AI Remote |
• Completed RLHF (Reinforcement Learning from Human Feedback) tasks by ranking and rating AIgenerated outputs to improve large language model quality.
• Annotated and evaluated responses for factual accuracy, coherence, tone, and instruction-following across
multiple prompt categories.
• Performed code review and debugging annotation tasks for Python and SQL outputs generated by AI
models.
• Maintained 95%+ quality score across 500+ completed tasks through strict adherence to platform
guidelines.
• Provided detailed written rationales for model feedback, contributing to fine-tuning pipelines for generative
2024 - 2024
Education
S
Shivaji University
Bachelor of Technology, Computer Science and Engineering (Data Science)
