Sam Nagajjanavar

AI / ML Engineer

Hanagal, Karnataka, India 2+ yrs exp 84 · Excellent

About

AI / ML Engineer with 1.9 years of experience in data science, NLP, and Generative AI. Has contributed to an AI-powered chatbot and a customer feedback system built on BERT, LLMs, and LangChain, and integrated backend APIs to bring AI/NLP functionality into web applications. Applies supervised classification, intent detection, and sentiment analysis, has worked on image processing for number plate recognition, and has built predictive and recommendation models with 88–92% accuracy. Skilled in Python, SQL, data preprocessing, feature engineering, and model evaluation, and works closely with development teams to deliver reliable, data-driven features and troubleshoot production issues.

Skills & Expertise (46)

Generative AI Models Intermediate

8.0/10

Years Exp

NLP Intermediate

8.0/10

Years Exp

Chatbot Development Intermediate

8.0/10

Years Exp

Python Intermediate

7.5/10

Years Exp

Model Evaluation Intermediate

7.0/10

Years Exp

Data Cleaning Intermediate

7.0/10

Years Exp

Feature Engineering Intermediate

7.0/10

Years Exp

API Integration Intermediate

7.0/10

Years Exp

scikit-learn Intermediate

7.0/10

Years Exp

SQL Intermediate

6.5/10

Years Exp

Git Intermediate

6.5/10

Years Exp

MySql YAML VS Code MongoDb REST APIs Power BI Tableau Backend Excel Hypothesis Testing Statistical Analysis EDA Matplotlib NumPy Seaborn Haar Cascade LLMs LangChain Prompt Engineering RAG AI Agents Vector Databases Sentiment Analysis BERT Image Processing Pandas Text Processing Regression Classification Clustering Logistic Regression Decision Tree Random Forest XGBoost Cross-Validation

Work Experience

Technical Analyst, Data Science & AI/ML

Prasanna Technologies Pvt Ltd

Dec 2024 - Present

Contributed to an AI-powered chatbot system involving NLP and BERT-based components. Built NLP solutions for a customer feedback and support system using BERT, LLMs, and LangChain. Integrated backend APIs to support AI/NLP functionality within the application. Implemented intent detection and classified customer feedback into positive, negative, and neutral sentiment categories, making support data easier to analyze. Collected customer feedback from the system and converted it into structured CSV datasets for analysis and modelling. Applied supervised classification models (Logistic Regression, Decision Tree, Random Forest) to customer feedback data, and tested XGBoost alongside them to compare model performance. Wrote SQL queries to retrieve, filter, and aggregate data used by application features and data displays. Implemented data-driven dashboards, charts, and tables within web applications based on defined requirements. Analyzed application logs to troubleshoot production issues and identify problems affecting functionality. Worked within a development team using VS Code, Git, YAML, DSL, and DbSolo in day-to-day application development.

Machine Learning Intern

1Stop.AI

Jun 2024 - Sep 2024

Developed a recommendation solution that achieved 92% prediction accuracy. Developed and evaluated machine learning models for prediction tasks using cross-validation and performance metrics. Cleaned and preprocessed soil and climate datasets, handling missing values and outliers and applying normalization where required. Performed exploratory data analysis to identify relationships, patterns, and characteristics within the data. Applied feature engineering and variable selection to support machine learning model development. Performed statistical analysis, including probability-based analysis and hypothesis testing. Used Python, Pandas, NumPy, Matplotlib, and Seaborn for analysis and visualization.