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Rajeev Nishad

Rajeev Nishad

Associate Software Developer - Artificial Intelligence & Machine Learning

INDIA flag
kanpur nagar, India
Entry Level

Key Skills

Software

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Top Subject Matter

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Top Data Types

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Top Label Types

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Freelancer Overview

I am a Computer Science undergraduate specializing in AI and Machine Learning, with hands-on experience in data processing, annotation, and building predictive models using Python, Scikit-Learn, Pandas, and NumPy. Through my internship and academic projects, I have worked extensively with real-world datasets, including developing a fake news detection system and a real-time face detection application, which involved preparing, cleaning, and labeling data for machine learning workflows. My strong foundation in data structures, algorithms, and coding, combined with my experience in computer vision and NLP domains, enables me to contribute effectively to high-quality AI training data and annotation tasks. I am detail-oriented, analytical, and passionate about ensuring data accuracy and integrity in AI projects.

Entry Level

Labeling Experience

Intent Labeler - Chatbot Intent Annotation Academic Project

TextClassification
For a general purpose chatbot project, I performed manual text classification and intent labeling. This involved structuring intent-response pairs and refining dataset coverage. My efforts improved the chatbot's response accuracy through enhanced data labeling. • Classified user queries by intent • Labeled examples for various chatbot intents • Analyzed query distribution for dataset refinement • Focused on intent-based annotation workflow

For a general purpose chatbot project, I performed manual text classification and intent labeling. This involved structuring intent-response pairs and refining dataset coverage. My efforts improved the chatbot's response accuracy through enhanced data labeling. • Classified user queries by intent • Labeled examples for various chatbot intents • Analyzed query distribution for dataset refinement • Focused on intent-based annotation workflow

2025 - 2025

Image Annotator - Real-time Face Detection Academic Project

ImageBounding Box
I managed and processed image datasets for a real-time face detection academic project. My work involved utilizing bounding box concepts to localize objects within images. I ensured each image was accurately labeled for training a Haar Cascade-based detection model. • Labeled positive and negative image samples • Marked bounding boxes for face/object localization • Maintained dataset quality for algorithm performance • Contributed to reliable model training data

I managed and processed image datasets for a real-time face detection academic project. My work involved utilizing bounding box concepts to localize objects within images. I ensured each image was accurately labeled for training a Haar Cascade-based detection model. • Labeled positive and negative image samples • Marked bounding boxes for face/object localization • Maintained dataset quality for algorithm performance • Contributed to reliable model training data

2025 - 2025

Text Annotator - Fake News Detection Academic Project

TextClassification
As part of an academic Fake News Detection project, I curated and cleaned a textual news dataset for binary classification. I performed annotation to verify and generate accurate ground truth labels. This ensured dataset uniformity and reliability for NLP-based model development. • Used Pandas and Scikit-Learn for text preprocessing • Validated text labels for true/false news classification • Manually annotated samples for label accuracy • Focused on clean, noise-free training data

As part of an academic Fake News Detection project, I curated and cleaned a textual news dataset for binary classification. I performed annotation to verify and generate accurate ground truth labels. This ensured dataset uniformity and reliability for NLP-based model development. • Used Pandas and Scikit-Learn for text preprocessing • Validated text labels for true/false news classification • Manually annotated samples for label accuracy • Focused on clean, noise-free training data

2025 - 2025

AI-ML Virtual Intern - Data Preprocessing & Labeling

TextClassification
During my AI-ML internship, I was responsible for the preprocessing and manual verification of raw textual datasets. I ensured high data quality and accuracy for downstream ML model training. My main focus was on dataset organization, quality assurance, and text classification. • Performed careful QA checks to validate ground truth labels • Automated data organization using Python (Pandas) • Collaborated with remote teams to meet dataset standards • Enhanced dataset consistency for improved model performance

During my AI-ML internship, I was responsible for the preprocessing and manual verification of raw textual datasets. I ensured high data quality and accuracy for downstream ML model training. My main focus was on dataset organization, quality assurance, and text classification. • Performed careful QA checks to validate ground truth labels • Automated data organization using Python (Pandas) • Collaborated with remote teams to meet dataset standards • Enhanced dataset consistency for improved model performance

2024 - 2024

Education

A

Axis Institute of Technology & Management, AKTU

Bachelor of Technology, Computer Science (Artificial Intelligence and Machine Learning)

Bachelor of Technology
2023

Work History

N

N/A

AI-ML Virtual Intern

N/A
2024 - 2024