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I am a Master’s student with hands-on experience in software development and machine learning. Currently, I work as a Teaching Assistant, mentoring students in data analytics, databases, and programming. I previously worked as a Machine Learning Engineer at Total Credit Recovery Ltd, where I contributed to developing and optimizing AI-driven solutions. I have also built several end-to-end projects, including a Sentiment Analysis API using Flask, MongoDB, and Docker. I’m passionate about building scalable systems and applying data-driven approaches to solve real-world problems.…I am a Master’s student with hands-on experience in software development and machine learning. Currently, I work as a Teaching Assistant, mentoring students in data analytics, databases, and programming. I previously worked as a Machine Learning Engineer at Total Credit Recovery Ltd, where I contributed to developing and optimizing AI-driven solutions. I have also built several end-to-end projects, including a Sentiment Analysis API using Flask, MongoDB, and Docker. I’m passionate about building scalable systems and applying data-driven approaches to solve real-world problems.

Yesha Shah

AI Developer, Web Developer, Full Stack Developer, +3

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I am a Master’s student with hands-on experience in software development and machine learning. Currently, I work as a Teaching Assistant, mentoring students in data analytics, databases, and programming. I previously worked as a Machine Learning Engineer at Total Credit Recovery Ltd, where I contributed to developing and optimizing AI-driven solutions. I have also built several end-to-end projects, including a Sentiment Analysis API using Flask, MongoDB, and Docker. I’m passionate about building scalable systems and applying data-driven approaches to solve real-world problems.…I am a Master’s student with hands-on experience in software development and machine learning. Currently, I work as a Teaching Assistant, mentoring students in data analytics, databases, and programming. I previously worked as a Machine Learning Engineer at Total Credit Recovery Ltd, where I contributed to developing and optimizing AI-driven solutions. I have also built several end-to-end projects, including a Sentiment Analysis API using Flask, MongoDB, and Docker. I’m passionate about building scalable systems and applying data-driven approaches to solve real-world problems.

Available to hire

I am a Master’s student with hands-on experience in software development and machine learning. Currently, I work as a Teaching Assistant, mentoring students in data analytics, databases, and programming. I previously worked as a Machine Learning Engineer at Total Credit Recovery Ltd, where I contributed to developing and optimizing AI-driven solutions. I have also built several end-to-end projects, including a Sentiment Analysis API using Flask, MongoDB, and Docker. I’m passionate about building scalable systems and applying data-driven approaches to solve real-world problems.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

Javanese

Advanced

Amharic

Advanced

Work Experience

Teaching Assistant at Concordia University

September 1, 2024 - Present

Led tutorials and labs on Databases, Data Analytics, C++ Programming, Artificial Intelligence, and Software Engineering; guided students in mastering SQL, design patterns, object-oriented programming, and algorithmic problem-solving; delivered sessions on Git, GitHub, CI/CD with GitHub Actions, and core web development concepts.

Teaching Assistant at Concordia University

September 1, 2024 - Present

Conducted tutorials and lab sessions for courses including Databases, Data Analytics, Programming and Problem Solving, and Software Process. Guided students through SQL, database normalization, MySQL queries, object-oriented programming, design patterns, and core data structures and algorithms. Assessed assignments, projects, and exams with detailed feedback to reinforce conceptual understanding and practical implementation.

Teaching Assistant at Concordia University Montreal

September 1, 2024 - Present

Assisted in tutorials and labs for courses including databases, data analytics, programming and problem solving, and software process. Guided students through SQL, database normalization, MySQL queries, object-oriented programming, design patterns, and core data structures and algorithms; assessed assignments and exams and provided detailed feedback.

Teaching Assistant at Concordia University

September 1, 2024 - Present

Conducted tutorials and lab sessions for courses including Databases, Data Analytics, Programming and Problem Solving, and Software Process; explained key concepts and guided hands-on exercises. Assessed assignments, projects, and exams with detailed feedback to enhance understanding of theoretical concepts and real-world implementation.

Teaching Assistant at Concordia University

September 1, 2024 - Present

Conducted tutorials and lab sessions for courses including databases, data analytics, programming and problem solving, and software process. Guided students through SQL, database normalization, MySQL queries, object-oriented programming, design patterns, and core data structures and algorithms. Assessed assignments, projects, and exams, providing detailed feedback to enhance understanding of theoretical concepts and real-world implementation.

AI Developer at TechnoHustlers PVT. LTD.

December 31, 2023 - October 15, 2025

Designed and maintained high-performance backend services using Flask and PostgreSQL, built secure RESTful APIs with JWT authentication and role-based access control; integrated machine learning models into production via FastAPI; implemented core MLOps workflows including model packaging with Docker and automated CI/CD pipelines.

AI Developer at TechnoHustlers PVT. LTD.

December 31, 2023 - October 15, 2025

Designed and maintained high-performance backend services using Flask and PostgreSQL. Developed secure, scalable RESTful APIs with JWT authentication and role-based access control. Integrated machine learning models into production using FastAPI. Implemented core MLOps workflows including model packaging with Docker, automated deployment via CI/CD pipelines, and performance monitoring to ensure scalable and reliable ML solutions.

Software Developer at TechnoHustlers Pvt. Ltd.

December 1, 2023 - October 20, 2025

Developed and optimized scalable backend services using Flask and PostgreSQL; built secure RESTful APIs with JWT authentication and integrated with React components; implemented robust error handling, timeout management, and input validation; used Git for version control and automated CI/CD workflows for faster releases.

AI Developer at TechnoHustlers PVT. LTD.

December 1, 2023 - October 15, 2025

Designed and maintained high-performance backend services using Flask and PostgreSQL, ensuring efficient data flow and seamless user experience. Developed secure, scalable RESTful APIs with JWT authentication and RBAC. Integrated ML models into production using FastAPI, enabling user behavior analysis and automated insights. Implemented MLOps workflows including model packaging with Docker, CI/CD deployment, and performance monitoring for scalable ML solutions.

AI Developer at TechnoHustlers PVT. LTD.

December 1, 2023 - October 15, 2025

Designed and maintained high-performance backend services using Flask and PostgreSQL; developed RESTful APIs with JWT authentication and role-based access control; integrated ML models into production using FastAPI; implemented MLOps workflows with Docker and CI/CD pipelines, plus monitoring.

Data Analytics and Machine Learning Intern at Infolabz IT Services PVT. LTD.

July 31, 2022 - October 15, 2025

Leveraged Scikit-Learn and Pandas to process 100,000+ data points; developed a data integration pipeline with Flask for ingestion from CSV, Excel, and API sources; built and optimized regression and classification models (Random Forest, SVM) with ~20% performance gains; evaluated models using metrics such as Accuracy, Precision, Recall, F1-score, ROC-AUC for classification and R-squared, MAE for regression.

Data Analytics and Machine Learning Intern at Infolabz IT Services PVT. LTD.

July 31, 2022 - October 15, 2025

Leveraged Scikit-Learn and Pandas to process 100,000+ data points, deriving actionable insights. Developed a data integration pipeline with Flask, streamlining data ingestion from CSV, Excel, and API sources. Built and optimized regression and classification models (e.g., Random Forest, SVM), achieving 20% performance gains. Evaluated models using metrics like Accuracy, Precision, Recall, F1-score, ROC-AUC for classification, and R-squared, MAE for regression.

Data Analytics and Machine Learning Intern at Infolabz IT Services Pvt. Ltd.

July 1, 2022 - October 20, 2025

Leveraged Scikit-Learn and Pandas to process 100,000+ data points; developed a data integration pipeline with Flask to ingest data from CSV, Excel, and API sources; built regression and classification models (Random Forest, SVM) achieving 20% performance gains; evaluated models using accuracy, precision, recall, F1-score, ROC-AUC, R-squared, and MAE.

Data Analytics and Machine Learning Intern at Infolabz IT Services PVT. LTD.

July 1, 2022 - October 15, 2025

Processed 100,000+ data points using Scikit-Learn and Pandas to derive actionable insights. Built a data integration pipeline with Flask to ingest data from CSV, Excel, and API sources. Developed regression and classification models (Random Forest, SVM) achieving ~20% performance gains and evaluated models withAccuracy, Precision, Recall, F1-score, ROC-AUC, as well as R-squared and MAE for regression.

Data Analytics and Machine Learning Intern at Infolabz IT Services PVT. LTD.

July 1, 2022 - October 15, 2025

Processed 100,000+ data points with Scikit-Learn and Pandas; built a data integration pipeline with Flask to ingest CSV, Excel, and API sources; developed regression and classification models (Random Forest, SVM) achieving ~20% performance gains; evaluated models with standard metrics.