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Machine Learning Engineer with less than a year in Python, ML algorithms, and full-stack development
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Assessing your cultural and operational fit
Aspiring Machine Learning Engineer and Computer Science student with a solid foundation in Python, machine learning algorithms, and model deployment. Passionate about building intelligent, data-driven solutions that solve real-world problems. Seeking a challenging role to apply ML and data science skills, contribute to collaborative agile teams, and grow in a dynamic, innovation-focused environment.
SRKR Engineering College
Bachelor of Technology
August 1, 2022 – June 30, 2026
Aditya Junior College
Pre-University Course
June 1, 2020 – May 31, 2022
Sri Chaitanya School
Secondary School Certificate
June 1, 2019 – May 31, 2020
Blackbucks
Full Stack Development Internship
March 1, 2026 – May 31, 2026
India
Crop Prediction
January 1, 2025 – December 31, 2025
Developed a crop prediction web application using Random Forest algorithm to suggest the most suitable crop based on soil and climate parameters. Built the frontend using Flask and rendered dynamic HTML templates to capture user input and display model predictions. Preprocessed and trained the model using a dataset containing features like nitrogen, phosphorus, potassium levels, temperature, humidity, and rainfall. Ensured model accuracy through evaluation metrics and fine-tuned hyperparameters for optimal performance. Deployed the application locally and demonstrated predictive insights to aid data-driven agricultural decision-making.
View ProjectHeart Disease Prediction
January 1, 2025 – December 31, 2025
Built and evaluated multiple supervised machine learning models including Logistic Regression, Decision Tree, Random Forest, Extra Trees, K-Nearest Neighbors, and Gaussian Naive Bayes using scikit-learn. Performed training and testing using consistent preprocessing to ensure fair model comparison. Generated confusion matrices and classification reports for each model to extract key metrics like accuracy, precision, recall, F1-score, specificity, and balanced accuracy. Visualized ROC curves for all models to compare trade-offs between sensitivity and specificity across different thresholds. Drew insights on model selection by interpreting evaluation results, identifying Random Forest as top performers on the dataset.
View ProjectFoodExpress – Online Food Ordering System
January 1, 2025 – December 31, 2025
Developed a dynamic web-based food ordering system using PHP and HTML to enable customers to browse restaurants, view menus, and place orders online. Implemented user authentication and personalized greetings using PHP sessions and MySQL for customer management. Designed and structured web pages with HTML and CSS to display restaurant listings, food items, and cart details responsively. Integrated features such as cart persistence, order placement, and real-time total calculation including delivery charges. Utilized MySQL for backend data storage including users, restaurants, food items, cart data, and order history.
View ProjectGetting Started with Competitive Coding
NPTEL
June 1, 2026 – Present
Programming essentials in Python
Cisco
June 1, 2026 – Present
Programming In Java
NPTEL
June 1, 2026 – Present
Cyber Security
Cisco
June 1, 2026 – Present
Programming essentials in C++
Cisco
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate an interest in applying machine learning to practical problems (heart disease, crop prediction) and also includes a full-stack web development project. This diversity shows a willingness to explore different areas of software development. However, the projects are all personal and relatively small scale, which might indicate a need for more experience in collaborative, larger-scale enterprise environments. The target role is Machine Learning Engineer, and the projects align well with the core technical requirements, but the overall experience level is very junior (experienceLevel: 0), which might not be a direct fit for a senior role without significant mentorship and growth.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on self-directed projects and a foundational understanding of project lifecycle from model building to deployment. The internship experience suggests exposure to an agile environment and collaboration. However, without specific psychometric or English test scores, it is difficult to fully assess logical reasoning, work attitude, stress handling, and team collaboration beyond basic inferences from project completion.