Krishan S.

Key Skills

Software

Don't disclose

Other

OpenCV AI Kit (OAK)

Top Subject Matter

NLP / Moderation (hate speech and profanity detection)

Deep learning text generation

Computer vision / Face detection & recognition

Top Data Types

Text

Image

Top Task Types

Classification

Text Generation

Object Detection

Relationship

Freelancer Overview

Hate Speech and Profane Language Detector (Python, Django, NLTK, Scikit-learn). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose, Other, and OpenCV AI Kit (OAK). Education includes Bachelor of Technology, Guru Jambheshwar University of Science & Technology (2025) and Professional Certificate, Google (2024). AI-training focus includes data types such as Text and Image and labeling workflows including Classification, Text Generation, and Object Detection.

Labeling Experience

Snappikart Techlabs (Django and Backend Intern)

Don't discloseText

Contributed backend development in Django/DRF with focus on secure, performant API design rather than direct annotation work. Worked on database design and wrote modular backend code following best practices. This experience supported data-driven application infrastructure used by ML/NLP features. • Developed RESTful APIs with Django REST Framework • Collaborated across multiple apps and contributed to schema/database design • Implemented best-practice considerations for API security and performance • Optimized response times and scalability for backend services

2025 - 2025

Hate Speech and Profane Language Detector (Python, Django, NLTK, Scikit-learn)

Don't discloseTextClassification

Built and optimized NLP-driven detection features for hate speech and profane language using Python-based ML. Implemented text preprocessing with NLTK and trained/evaluated a Scikit-learn model to classify harmful vs. non-harmful text. Designed the application for use in social media moderation and research workflows. • Ingested and processed raw text inputs for model training/inference • Applied text feature extraction and model training with Scikit-learn • Tuned thresholds/accuracy to support high-accuracy classification • Packaged detection logic into a Django web application workflow

2025 - 2025

Bolt Iot (Full stack developer intern) and dating application backend project (Python, Django, PostgreSQL)

Don't discloseTextRelationship

Implemented a backend for a dating application that enforces authorization and security constraints for application access. Built server-side functionality using Python and Django with PostgreSQL as the data store. While not an annotation role, the backend required structuring and handling relational user/app interactions. • Designed and implemented Django backend endpoints and data models • Enforced security measures for authorized access • Managed PostgreSQL persistence for application features • Collaborated on backend operations to support application functionality

2023 - 2023

Face detection and recognition system (Python, Django, Dlib, OpenCV, NumPy)

OpenCV AI Kit (OAK)ImageObject Detection

Created a real-time face detection and recognition system using computer vision and deep learning libraries. Combined Dlib with OpenCV and NumPy for face localization/recognition, then connected results to a Django web interface. Reported detection and recognition accuracies to demonstrate model performance. • Implemented face detection pipeline with OpenCV/Dlib • Added recognition logic to identify faces with reported accuracy • Integrated model outputs into Django for web-based interaction • Supported real-time inference behavior for live inputs

2022

Word-Level Text Generator (Python, TensorFlow, Keras, Pandas, NumPy)

OtherTextText Generation

Developed a word-level text generation model using deep learning components in Python. Used TensorFlow/Keras with data processing via Pandas and NumPy to generate context-specific text sequences. Evaluated outputs for potential downstream uses like chatbots and translation-related generation. • Prepared datasets and text representations for word-level modeling • Built and trained neural network layers in Keras • Generated context-specific text sequences from input prompts • Integrated the modeling workflow as a reusable project artifact

2022

Education

Work History