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Machine Learning Engineer with 1+ years in AI & Deep Learning
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Detail-oriented Software Engineer with a strong foundation in designing, developing, and optimizing scalable software solutions. Skilled in problem-solving, writing clean and efficient code, and working collaboratively in agile environments to deliver high- quality products.
Sri Vasavi Engineering College
B-Tech
August 1, 2021 – June 30, 2025
Narayana English Medium School
SSC
June 1, 2018 – May 31, 2019
Sabio Infotech Inc.
Jr.Machine Learning Engineer
December 1, 2025 – Present
Hyderābād, Telangana, India
HEALTH LIFE STYLE CLASSIFICATION
June 1, 2026 – June 1, 2026
Developed a health lifestyle classification model using machine learning to categorize individuals based on health and lifestyle patterns. Applied data preprocessing, feature engineering, and model evaluation to improve prediction accuracy and support preventive healthcare insights.
SMART PRICING MODEL FOR SECOND-HAND CARS
June 1, 2026 – June 1, 2026
Built a smart pricing model for second-hand cars by experimenting with multiple machine learning algorithms (Linear Regression, Random Forest, XGBoost, etc.). Performed data preprocessing, feature engineering, and model comparison to identify the best-performing approach for accurate price prediction.
DASHBOARD FOR SMART PRICING MODEL FOR SECOND-HAND CARS USING POWER BI
June 1, 2026 – June 1, 2026
Developed a Smart Pricing Dashboard for second-hand cars using Power BI, integrating market data and predictive model outputs to provide fair price recommendations, analyze demand trends, and support data-driven sales decisions
EMPLOYEE ANNUAL SALARY PREDICTION
June 1, 2026 – June 1, 2026
Implemented an employee annual salary prediction model using machine learning techniques to estimate salaries based on agentID, agent name, grosspay and job role. Performed data preprocessing, feature selection, and model evaluation to ensure accurate predictions.
IMAGE CLASSIFICATION
June 1, 2026 – June 1, 2026
Developed a flower image classification model using PCA for dimensionality reduction and SVM for classification. Enhanced model efficiency and accuracy through feature extraction, preprocessing, and performance evaluation.
HAND WRITTEN DIGIT RECOGNITION USING CNN
June 1, 2026 – June 1, 2026
Developed a deep learning model using CNN to recognize handwritten digits (0-9) from images. Trained the model on the MNIST dataset with image preprocessing and normalization, achieving high classification accuracy and demonstrating effective image-based pattern recognition.
AI EMAIL GENERATOR USING GEN AI
June 1, 2026 – June 1, 2026
Developed a Generative AI-based application that automatically creates professional, context-aware emails based on user intent and tone, helping users generate high-quality email drafts efficiently.
AI-ML-DS internship Certificate
Unknown
June 1, 2026 – Present
AICTE-Emerging Technologies (AI & Cloud)
AICTE
June 1, 2026 – Present
Data Science Course completion certificate
Unknown
June 1, 2026 – Present
The candidate scored 94% on the 'Data Scientist — Artificial Intelligence' exam, indicating a very strong grasp of the subject matter and related skills.
Strengths
Limitations
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest and initiative in various Machine Learning and AI applications, including image recognition, classification, and generative AI. The professional experience as a Jr. Machine Learning Engineer aligns well with the target role, indicating a clear career path and dedication to the field. The diversity of projects, from traditional ML to deep learning and generative AI, suggests adaptability and a broad interest in emerging technologies.
Soft Skills & Operational Fit
The candidate's profile highlights a detail-oriented approach, problem-solving skills, and collaborative work in agile environments. The psychometric test score (184/500) suggests potential areas for development in logical reasoning, work attitude, stress handling, or team collaboration, which would require further investigation during an interview.