Help & Supportcareers@gravityer.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer with 3+ years in data engineering, machine learning & AI systems.
Data professional with 3+ years of experience in data engineering and machine learning, building scalable ETL pipelines, analytics platforms, and ML-ready datasets in enterprise environments. Proficient in Python, SQL, Informatica PowerCenter, AWS, and Tableau for developing data pipelines and analytics solutions. Hands-on experience in predictive modeling, anomaly detection, and LLM-powered Retrieval-Augmented Generation (RAG) systems using embeddings and FAISS vector databases. Recognized as Value Champion of the Quarter for delivering scalable, high-quality data solutions.
Bishop Heber College
Bachelor of Vocational · Information Technology
August 1, 2019 – June 30, 2022
Prodapt Solutions Pvt. Ltd.
Machine Learning Engineer | Data Scientist
September 1, 2022 – Present
Chennai, Tamil Nadu, India
Credit Risk Prediction System
January 1, 2024 – June 1, 2026
• Developed an end-to-end Credit Risk Prediction System to identify customers with a high probability of loan default using the Home Credit Default Risk dataset. • Designed and implemented a PostgreSQL-based data storage layer by loading and managing 11 financial datasets containing customer demographics, credit history, loan applications, and repayment information. • Built customer-level feature engineering pipelines by aggregating bureau records, previous loan applications, and repayment history into a single machine-learning-ready dataset. • Performed extensive data preprocessing, including missing value treatment, categorical variable encoding, feature selection, and data quality validation. • Trained and evaluated multiple machine learning models including Logistic Regression, Random Forest, and XGBoost to predict customer default probability. • Addressed class imbalance using class weighting techniques and evaluated model performance using ROC-AUC, Precision, Recall, F1-Score, and Accuracy metrics. • Developed a real-time prediction API using FastAPI, enabling risk assessment for individual customers through REST endpoints and Swagger UI. • Implemented model persistence, feature pipeline integration, and GitHub-based version control, along with comprehensive technical documentation and architecture design.
View ProjectAI-Powered KOL (Key Opinion Leader) Recommendation System | Generative AI Project
January 1, 2024 – June 1, 2026
• Developed an end-to-end AI-powered KOL Recommendation System to identify and recommend domain experts using semantic search and hybrid ranking techniques. • Collected and processed researcher data from OpenAlex API, built researcher profiles, and stored structured data in PostgreSQL. • Generated vector embeddings using Sentence Transformers (all-MiniLM-L6-v2) and implemented semantic similarity search using FAISS Vector Database. • Designed a hybrid ranking algorithm combining semantic similarity, citation count, and H-index scores to improve recommendation quality and researcher relevance. • Integrated Phi3 Mini LLM through Ollama to generate AI-powered explanations for researcher recommendations. • Built REST APIs using FastAPI and developed an interactive Streamlit dashboard for real-time researcher discovery and recommendation visualization.
View ProjectPython Essential Training
Udemy
January 1, 2025 – Present
Python for Data Science and Machine Learning Bootcamp
Udemy
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's experience spans traditional machine learning, data engineering, and cutting-edge generative AI projects, demonstrating adaptability and a willingness to learn new technologies. The diversity of projects (credit risk, KOL recommendation, RAG chatbot) indicates a broad interest in applying ML/AI to different domains, which aligns well with dynamic, innovation-driven environments. The focus on end-to-end solutions and collaboration suggests a team-oriented mindset.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration with data engineers, analysts, and stakeholders, indicating good teamwork and communication skills. The 'Value Champion of the Quarter' award suggests a strong work ethic and ability to deliver high-quality solutions. The project descriptions show a structured approach to problem-solving and attention to detail in system design and documentation.