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Baskar B.

@baskarrajendran

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AI/ML Engineer | SEO Expert | Python | Automation

$25 USD / Hour

・

Flag of

India (1:14 PM)

・

Joined on November 16, 2025

$25 USD / Hour

・

I am பாஸ்கர் (Baskar) , AI/MLEngineer specializing in Generative AI, LLMs, and Machine Learning. Proficient in Transformers, LangChain, and CrewAI for building scalable AI solutions. Experienced in developing AI-driven applications leveraging Large Language Models (LLMs) to automate tasks, enhance decision-making, and improve user interactions. Passionate about advancing AI capabilities through cutting-edge generative models and intelligent systems Portfolios and Demos: [login to view URL] [login to view URL] [login to view URL]

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Portfolio

Portfolio

13709421
This project is an Ad Clicker Automation System designed to automate tasks related to ad interactions, search engine operations, and data collection. It consists of a backend and a frontend, each serving specific purposes: Backend: Built with Django and Celery, the backend handles task scheduling, data processing, and automation logic. Key components include: Task Automation: Scripts for automating ad clicks and search engine interactions. Database: SQLite database (db.sqlite3) for storing configurations and logs. Celery: Manages background tasks like periodic data collection. Media Files: Stores debug HTML files and screenshots for analysis. APIs: Provides endpoints for the frontend to interact with backend services. Frontend: Developed with React, the frontend offers a user-friendly interface for managing and monitoring automation tasks. Key features include: Dashboard: Displays task statuses and analytics. Configuration Panels: Allows users to set up keywords, target websites, and

Google Ad Clicker Automation System

This project is an Ad Clicker Automation System designed to automate tasks related to ad interactions, search engine operations, and data collection. It consists of a backend and a frontend, each serving specific purposes: Backend: Built with Django and Celery, the backend handles task scheduling, data processing, and automation logic. Key components include: Task Automation: Scripts for automating ad clicks and search engine interactions. Database: SQLite database (db.sqlite3) for storing configurations and logs. Celery: Manages background tasks like periodic data collection. Media Files: Stores debug HTML files and screenshots for analysis. APIs: Provides endpoints for the frontend to interact with backend services. Frontend: Developed with React, the frontend offers a user-friendly interface for managing and monitoring automation tasks. Key features include: Dashboard: Displays task statuses and analytics. Configuration Panels: Allows users to set up keywords, target websites, and

Google Ad Clicker Automation System

This project is an Ad Clicker Automation System designed to automate tasks related to ad interactions, search engine operations, and data collection. It consists of a backend and a frontend, each serving specific purposes: Backend: Built with Django and Celery, the backend handles task scheduling, data processing, and automation logic. Key components include: Task Automation: Scripts for automating ad clicks and search engine interactions. Database: SQLite database (db.sqlite3) for storing configurations and logs. Celery: Manages background tasks like periodic data collection. Media Files: Stores debug HTML files and screenshots for analysis. APIs: Provides endpoints for the frontend to interact with backend services. Frontend: Developed with React, the frontend offers a user-friendly interface for managing and monitoring automation tasks. Key features include: Dashboard: Displays task statuses and analytics. Configuration Panels: Allows users to set up keywords, target websites, and

Google Ad Clicker Automation System

This project is an Ad Clicker Automation System designed to automate tasks related to ad interactions, search engine operations, and data collection. It consists of a backend and a frontend, each serving specific purposes: Backend: Built with Django and Celery, the backend handles task scheduling, data processing, and automation logic. Key components include: Task Automation: Scripts for automating ad clicks and search engine interactions. Database: SQLite database (db.sqlite3) for storing configurations and logs. Celery: Manages background tasks like periodic data collection. Media Files: Stores debug HTML files and screenshots for analysis. APIs: Provides endpoints for the frontend to interact with backend services. Frontend: Developed with React, the frontend offers a user-friendly interface for managing and monitoring automation tasks. Key features include: Dashboard: Displays task statuses and analytics. Configuration Panels: Allows users to set up keywords, target websites, and

Google Ad Clicker Automation System

13694571
A Python-based GUI application that analyzes C++ code for loop structures and generates a visual model of the iteration space to support optimization in high-performance and parallel computing. The tool automatically detects nested for loops, extracts iteration bounds, and displays iteration domains using interactive charts. The interface allows users to select loops, adjust iteration ranges, and preview the visual partitioning of iteration spaces. This PoC demonstrates core capabilities while establishing a foundation for upcoming features including advanced dependence analysis, ISLPY-driven polyhedral modeling, islplot visualization, and exportable LaTeX reports for performance engineering documentation. Designed to assist compiler engineers, research teams, and parallelization developers in analyzing and optimizing compute-intensive loops.

Automated C++ Loop Iteration Analysr

13693995
I managed a complete SEO content creation workflow for multiple websites, including keyword research, optimization, and performance tracking. Using real-time trending keyword data, I created SEO-optimized articles designed for discoverability and audience relevance. Each article went through structured optimization including on-page SEO, metadata, readability improvements, and internal linking suggestions. As a result, the content consistently achieved 85–89% SEO performance scores, positioning pages for higher keyword rankings and organic traffic growth. Key Contributions: • Trending keyword discovery based on market demand • Fully SEO-optimized article generation • Internal and external link strategy improvements • Meta title + description optimization • Optimization audits with measurable scoring results Outcome: Strong foundational SEO with scalable content that supports improved search visibility, ranking velocity, and long-term organic traffic growth

SEO-Optimized Content Creation

I managed a complete SEO content creation workflow for multiple websites, including keyword research, optimization, and performance tracking. Using real-time trending keyword data, I created SEO-optimized articles designed for discoverability and audience relevance. Each article went through structured optimization including on-page SEO, metadata, readability improvements, and internal linking suggestions. As a result, the content consistently achieved 85–89% SEO performance scores, positioning pages for higher keyword rankings and organic traffic growth. Key Contributions: • Trending keyword discovery based on market demand • Fully SEO-optimized article generation • Internal and external link strategy improvements • Meta title + description optimization • Optimization audits with measurable scoring results Outcome: Strong foundational SEO with scalable content that supports improved search visibility, ranking velocity, and long-term organic traffic growth

SEO-Optimized Content Creation

13709421
This project is an Ad Clicker Automation System designed to automate tasks related to ad interactions, search engine operations, and data collection. It consists of a backend and a frontend, each serving specific purposes: Backend: Built with Django and Celery, the backend handles task scheduling, data processing, and automation logic. Key components include: Task Automation: Scripts for automating ad clicks and search engine interactions. Database: SQLite database (db.sqlite3) for storing configurations and logs. Celery: Manages background tasks like periodic data collection. Media Files: Stores debug HTML files and screenshots for analysis. APIs: Provides endpoints for the frontend to interact with backend services. Frontend: Developed with React, the frontend offers a user-friendly interface for managing and monitoring automation tasks. Key features include: Dashboard: Displays task statuses and analytics. Configuration Panels: Allows users to set up keywords, target websites, and

Google Ad Clicker Automation System

This project is an Ad Clicker Automation System designed to automate tasks related to ad interactions, search engine operations, and data collection. It consists of a backend and a frontend, each serving specific purposes: Backend: Built with Django and Celery, the backend handles task scheduling, data processing, and automation logic. Key components include: Task Automation: Scripts for automating ad clicks and search engine interactions. Database: SQLite database (db.sqlite3) for storing configurations and logs. Celery: Manages background tasks like periodic data collection. Media Files: Stores debug HTML files and screenshots for analysis. APIs: Provides endpoints for the frontend to interact with backend services. Frontend: Developed with React, the frontend offers a user-friendly interface for managing and monitoring automation tasks. Key features include: Dashboard: Displays task statuses and analytics. Configuration Panels: Allows users to set up keywords, target websites, and

Google Ad Clicker Automation System

This project is an Ad Clicker Automation System designed to automate tasks related to ad interactions, search engine operations, and data collection. It consists of a backend and a frontend, each serving specific purposes: Backend: Built with Django and Celery, the backend handles task scheduling, data processing, and automation logic. Key components include: Task Automation: Scripts for automating ad clicks and search engine interactions. Database: SQLite database (db.sqlite3) for storing configurations and logs. Celery: Manages background tasks like periodic data collection. Media Files: Stores debug HTML files and screenshots for analysis. APIs: Provides endpoints for the frontend to interact with backend services. Frontend: Developed with React, the frontend offers a user-friendly interface for managing and monitoring automation tasks. Key features include: Dashboard: Displays task statuses and analytics. Configuration Panels: Allows users to set up keywords, target websites, and

Google Ad Clicker Automation System

This project is an Ad Clicker Automation System designed to automate tasks related to ad interactions, search engine operations, and data collection. It consists of a backend and a frontend, each serving specific purposes: Backend: Built with Django and Celery, the backend handles task scheduling, data processing, and automation logic. Key components include: Task Automation: Scripts for automating ad clicks and search engine interactions. Database: SQLite database (db.sqlite3) for storing configurations and logs. Celery: Manages background tasks like periodic data collection. Media Files: Stores debug HTML files and screenshots for analysis. APIs: Provides endpoints for the frontend to interact with backend services. Frontend: Developed with React, the frontend offers a user-friendly interface for managing and monitoring automation tasks. Key features include: Dashboard: Displays task statuses and analytics. Configuration Panels: Allows users to set up keywords, target websites, and

Google Ad Clicker Automation System

13694571
A Python-based GUI application that analyzes C++ code for loop structures and generates a visual model of the iteration space to support optimization in high-performance and parallel computing. The tool automatically detects nested for loops, extracts iteration bounds, and displays iteration domains using interactive charts. The interface allows users to select loops, adjust iteration ranges, and preview the visual partitioning of iteration spaces. This PoC demonstrates core capabilities while establishing a foundation for upcoming features including advanced dependence analysis, ISLPY-driven polyhedral modeling, islplot visualization, and exportable LaTeX reports for performance engineering documentation. Designed to assist compiler engineers, research teams, and parallelization developers in analyzing and optimizing compute-intensive loops.

Automated C++ Loop Iteration Analysr

13693995
I managed a complete SEO content creation workflow for multiple websites, including keyword research, optimization, and performance tracking. Using real-time trending keyword data, I created SEO-optimized articles designed for discoverability and audience relevance. Each article went through structured optimization including on-page SEO, metadata, readability improvements, and internal linking suggestions. As a result, the content consistently achieved 85–89% SEO performance scores, positioning pages for higher keyword rankings and organic traffic growth. Key Contributions: • Trending keyword discovery based on market demand • Fully SEO-optimized article generation • Internal and external link strategy improvements • Meta title + description optimization • Optimization audits with measurable scoring results Outcome: Strong foundational SEO with scalable content that supports improved search visibility, ranking velocity, and long-term organic traffic growth

SEO-Optimized Content Creation

I managed a complete SEO content creation workflow for multiple websites, including keyword research, optimization, and performance tracking. Using real-time trending keyword data, I created SEO-optimized articles designed for discoverability and audience relevance. Each article went through structured optimization including on-page SEO, metadata, readability improvements, and internal linking suggestions. As a result, the content consistently achieved 85–89% SEO performance scores, positioning pages for higher keyword rankings and organic traffic growth. Key Contributions: • Trending keyword discovery based on market demand • Fully SEO-optimized article generation • Internal and external link strategy improvements • Meta title + description optimization • Optimization audits with measurable scoring results Outcome: Strong foundational SEO with scalable content that supports improved search visibility, ranking velocity, and long-term organic traffic growth

SEO-Optimized Content Creation

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Experience

AI/ML Engineer

Aug, 2023 - Mar, 2025

•

1 year, 7 months

Adople AI

Aug, 2023 - Mar, 2025

•

1 year, 7 months

AI/MLEngineer specializing in Generative AI, LLMs, and Machine Learning. Proficient in Transformers, LangChain, and CrewAI for building scalable AI solutions. Experienced in developing AI-driven applications leveraging Large Language Models (LLMs) to automate tasks, enhance decision-making, and improve user interactions. Passionate about advancing AI capabilities through cutting-edge generative models and intelligent systems

Flag of

Bengaluru, India

Aug, 2023 - Mar, 2025

•

1 year, 7 months

Education

Periyar University

2023 - 2026

•

3 years

Bsc.Computer Science

Flag of

India

2023 - 2026

•

3 years

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