Anvesh Dubey

Key Skills

Software

AWS SageMaker

Appen

iMerit

Lionbridge

Mercor

Mindrift

OneForma

SuperAnnotate

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Geospatial Tiled Imagery

Text

Video

Top Label Types

RLHF

Evaluation Rating

Data Collection

Prompt Response Writing SFT

Transcription

Question Answering

Computer Programming Coding

Function Calling

Audio Recording

Segmentation

Bounding Box

Polygon

Polyline

Freelancer Overview

I am an AI Engineer and Data Analyst with hands-on experience in data annotation, labeling, and curation for advanced AI and machine learning projects. My background includes 3D mesh generation and annotation for computer vision, video and image dataset labeling for Meta’s video encoder, and large-scale data preparation for NLP and generative AI models. I am skilled in using tools such as CVAT, Amazon Mechanical Turk, and Meta AI platforms, and have contributed to projects involving object segmentation, prompt engineering, and quality control for high-precision datasets. My expertise spans across domains like e-commerce, digital publishing, and content moderation, and I am proficient with Python, PyTorch, TensorFlow, SQL, and visualization tools like Power BI and Tableau. I am passionate about ensuring data quality and consistency, and I thrive in collaborative, fast-paced environments where I can support the development of robust AI systems through meticulous data preparation and annotation.

Labeling Experience

AI tutor data science

MindriftTextQuestion AnsweringComputer Programming Coding

Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare). Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn). Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validatio

Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare). Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn). Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validatio

2024 - 2024

subject matter expert

OneformaVideoSegmentation

Evaluate LLM-generated responses for: Factual accuracy Logical consistency Helpfulness and completeness Safety, bias, and policy compliance Rank multiple AI responses based on defined quality rubrics Identify hallucinations, reasoning errors, and unsafe outputs Perform text-based data annotation and labeling tasks Apply prompt evaluation and refinement techniques to test AI behavior Complete qualifier, calibration, and benchmark tasks to access live workloads Follow strict annotation guidelines, scoring criteria, and project instructions Maintain high accuracy, consistency, and review acceptance rates Log work hours and task completion using platform-integrated tracking systems

Evaluate LLM-generated responses for: Factual accuracy Logical consistency Helpfulness and completeness Safety, bias, and policy compliance Rank multiple AI responses based on defined quality rubrics Identify hallucinations, reasoning errors, and unsafe outputs Perform text-based data annotation and labeling tasks Apply prompt evaluation and refinement techniques to test AI behavior Complete qualifier, calibration, and benchmark tasks to access live workloads Follow strict annotation guidelines, scoring criteria, and project instructions Maintain high accuracy, consistency, and review acceptance rates Log work hours and task completion using platform-integrated tracking systems

2025 - 2025

Ai tutor QA analyst

TelusTextComputer Programming CodingData Collection

Perform AI response evaluation and ranking based on accuracy, relevance, helpfulness, and safety Review and assess LLM-generated content against defined quality and policy rubrics Create and refine prompts to test AI reasoning, logic, and edge-case behavior Conduct text, image, and audio annotation tasks as per project requirements Label datasets accurately to support supervised and reinforcement learning workflows Follow strict annotation guidelines and quality standards Complete qualifier and calibration tasks to access live project work Ensure compliance with data security, confidentiality, and platform usage policies Track working hours and task completion via FTS (Field Task System) or Hubstaff when applicable Collaborate asynchronously with reviewers, QA teams, and project managers

Perform AI response evaluation and ranking based on accuracy, relevance, helpfulness, and safety Review and assess LLM-generated content against defined quality and policy rubrics Create and refine prompts to test AI reasoning, logic, and edge-case behavior Conduct text, image, and audio annotation tasks as per project requirements Label datasets accurately to support supervised and reinforcement learning workflows Follow strict annotation guidelines and quality standards Complete qualifier and calibration tasks to access live project work Ensure compliance with data security, confidentiality, and platform usage policies Track working hours and task completion via FTS (Field Task System) or Hubstaff when applicable Collaborate asynchronously with reviewers, QA teams, and project managers

2025 - 2025

AI Evaluation and Annotation QA Specialist

Aws SagemakerVideoRLHFEvaluation Rating

This role involved evaluating AI and GenAI model outputs, focusing on large language models and computer vision systems. I ensured annotation quality and consistency, contributing to AI training data pipelines and model improvement. Results were translated into KPIs, SOPs, and business-ready insights for stakeholders. • Evaluated LLM and CV model outputs for accuracy and relevance. • Performed annotation quality assurance and data pipeline support. • Generated feedback for continuous model improvements. • Created dashboards mapping AI performance to business goals.

This role involved evaluating AI and GenAI model outputs, focusing on large language models and computer vision systems. I ensured annotation quality and consistency, contributing to AI training data pipelines and model improvement. Results were translated into KPIs, SOPs, and business-ready insights for stakeholders. • Evaluated LLM and CV model outputs for accuracy and relevance. • Performed annotation quality assurance and data pipeline support. • Generated feedback for continuous model improvements. • Created dashboards mapping AI performance to business goals.

2024 - 2025

subject matter expert

SuperannotateVideoBounding BoxPolygon

Annotate images and video frames using polygon and bounding box techniques to accurately identify objects, regions, and boundaries Draw precise polygons around irregular object shapes to ensure pixel-level accuracy Create tight bounding boxes aligned to object edges as per annotation guidelines Label multiple object classes consistently across datasets Handle occluded, truncated, and overlapping objects accurately Apply correct class taxonomy and attribute tags to each annotation Maintain annotation accuracy across varying lighting, angles, resolutions, and environments Follow project-specific rubrics, labeling standards, and quality benchmarks Perform frame-by-frame annotation for video datasets when required Review and correct annotations based on QA feedback and audit results Identify and flag ambiguous or low-quality data for review Ensure 100% dataset coverage with no missing or misclassified objects Maintain high consistency and precision across large annotation

Annotate images and video frames using polygon and bounding box techniques to accurately identify objects, regions, and boundaries Draw precise polygons around irregular object shapes to ensure pixel-level accuracy Create tight bounding boxes aligned to object edges as per annotation guidelines Label multiple object classes consistently across datasets Handle occluded, truncated, and overlapping objects accurately Apply correct class taxonomy and attribute tags to each annotation Maintain annotation accuracy across varying lighting, angles, resolutions, and environments Follow project-specific rubrics, labeling standards, and quality benchmarks Perform frame-by-frame annotation for video datasets when required Review and correct annotations based on QA feedback and audit results Identify and flag ambiguous or low-quality data for review Ensure 100% dataset coverage with no missing or misclassified objects Maintain high consistency and precision across large annotation

2022 - 2025

Education

Work History