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C Machine Learning Engineer AI Models Training with less than a year in AI model training & data ann
Data science and machine learning practitioner with around 0+ years of experience in AI model training and data annotation. Delivered predictive models in Python, TensorFlow and Scikit learn that improved training quality, and designed Tableau dashboards that surfaced key patterns for operational decisions. Combined analytical thinking with meticulous data processing to support data driven outcomes.
Sri Venkateswara College of Engineering, SVCK
B.Tech · Computer Science & Engineering (AI & ML)
August 1, 2022 – June 30, 2026
Balavikas E. M. High, AP Board
SSC · Class X
June 1, 2020 – May 31, 2020
Sri Chaitanya Junior College
Intermediate · Class XII
June 1, 2020 – May 31, 2022
Smart Bridge
Data Analytics Intern
April 1, 2025 – June 1, 2025
India
Infosys
Artificial Intelligence Intern
November 1, 2024 – January 1, 2025
India
Identifying Rotten Fruits And Vegetables
June 20, 2026 – Present
Developed a computer vision web dashboard using Streamlit and TensorFlow/Keras to automate the detection of rotten fruits and vegetables by classifying image uploads against a custom deep learning model. Engineered a real-time data preprocessing pipeline leveraging Pillow and NumPy to standardize raw image files into unified 64x64 matrices, ensuring quick inference speed and high prediction accuracy. Designed a responsive UI with dynamic theme routing by injecting native HTML/CSS styles and using Base64 encoders, creating a clean user experience for selecting pages, checking dataset metrics, and viewing classification results.
Audio To Sign Language Translator
June 20, 2026 – Present
Designed a multi-view Tableau dashboard visualising Netflix content trends by release year, country of origin, and genre distribution, enabling fast identification of content gaps and popular categories. Engineered a scalable backend architecture using the Django web framework to power an administrative ecosystem for processing project assets and managing relational database pipelines. Streamlined application configuration and environmental management by optimizing custom Python execution pathways and configuring secure settings modules for local development environments.
Diabetes PredictionSystem
June 20, 2026 – Present
Implemented real-time model inference by serializing a predictive model and feature scaler using Pickle, reducing latency during live application testing. Designed a dynamic scoring algorithm that calculates and outputs percentage-based health risk factors directly to the user interface, improving data transparency.
Handwritten Digit Recognition
June 20, 2026 – Present
Designed and trained a Convolutional Neural Network to classify handwritten digits on the MNIST dataset (70,000 images), gaining practical experience in image preprocessing, batch normalisation, and model tuning.
Introduction to Data Analytics
IBM
June 1, 2026 – Present
Machine Learning Course Completion
Infosys Springboard
June 1, 2026 – Present
Machine Learning Internship
Infosys Springboard
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in AI/ML applications, aligning well with the target role. The diversity of projects (computer vision, NLP, predictive systems, data analytics) indicates a broad curiosity and willingness to explore different domains within AI. The internships at Smart Bridge and Infosys show an initiative to gain practical experience. However, the experience level is 0, suggesting a need for mentorship and structured guidance in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on diverse tasks, from model development to UI design and data visualization. The internship experiences suggest an understanding of applying academic knowledge to real-world datasets and optimizing solutions. However, the psychometric test score is not provided, making it difficult to assess logical reasoning, work attitude, stress handling, and team collaboration comprehensively.