Headline

Specialist Programmer @Infosys | Amazon ML Summer School ’25 | HackWithInfy Finalist ’25 | React.js, Python, Java SpringBoot & C++ | 1200+ DSA | B.Tech NIT Rourkela’26

About

I build full-stack web apps that scale — from a conference portal serving hundreds of users with zero downtime to a real-time ride-sharing platform with Stripe payments and Socket.io. Currently a Specialist Programmer Intern at Infosys and an alumnus of Amazon ML Summer School '25 (top 3,000 in India), I bring together 1,200+ DSA problems solved, hands-on ML experience, and a track record of shipping production-grade code with React, Spring Boot, Java, and Python. I'm a final-year Biomedical Engineering student at NIT Rourkela (CGPA 8.23) looking for full-time SDE roles starting 2026. If you're hiring engineers who can own a feature end-to-end — let's connect.

Location

Raurkela

AI stack

aistudio

kilocode

livekit

obsidian

Work experience

Specialist Programmer at Infosys, Jun 2026 - Present · 1 mo, Mysore

Specialist Programmer Intern at Infosys, Jan 2026 - Apr 2026 · 4 mos, Bengaluru

Trainee at Amazon ML Summer School, Aug 2025 - Oct 2025 · 3 mos, Selected among the Top 3000 students in India for Amazon ML Summer School 2025. Gained hands-on experience in Machine Learning, Deep Learning, and Applied AI through lectures and labs by Amazon scientists. Worked on case studies in recommendation systems, computer vision, and NLP, applying concepts to real-world datasets. Strengthened practical skills in Python, ML algorithms, and model deployment with industry-oriented mentorship.

Machine Learning Intern at Edunet Foundation, Jun 2025 - Jul 2025 · 2 mos, India, IBM SkillsBuild & Edunet Foundation Project: Employee Salary Prediction System 🔹 Overview: Working on a full-cycle supervised machine learning project to predict employee salaries based on structured HR data. Leveraging regression algorithms to support data-driven decision-making in hiring and compensation. 🔧 Key Responsibilities & Contributions: Data Acquisition & Preprocessing: Collected and cleaned a real-world HR dataset (5,000+ records), ensuring consistency and readiness for model training using Pandas and NumPy. Exploratory Data Analysis (EDA): Performed extensive EDA using Matplotlib and Seaborn to visualize distributions, correlations, and outliers impacting salary patterns. Feature Engineering: Created and transformed variables (e.g., ordinal encoding, log transformations) to improve model performance. Addressed missing values using statistical imputation. Model Development: Implemented and fine-tuned regression models including Linear Regression, Ridge, Lasso, and Decision Tree Regressors using scikit-learn. Model Evaluation: Validated models using cross-validation, R² Score, MAE, and RMSE. Compared performance metrics to select the best-fit model. Insights & Reporting: Communicated findings through Jupyter Notebook dashboards with clear visualizations and actionable insights for non-technical stakeholders. 🛠 Tools & Technologies: Python, Jupyter Notebook, Pandas, NumPy, scikit-learn, Matplotlib, Seaborn 📈 Key Learnings: Hands-on experience with end-to-end ML workflows — from data ingestion to model deployment readiness. Improved understanding of feature impact, model interpretability, and data pipeline design. Strengthened ability to explain complex ML insights to both technical and non-technical audiences.

Management Trainee at Skilled Sapiens, May 2025 - May 2025 · 1 mo, India, As a Management Trainee at Skilled Sapiens, I am gaining hands-on experience in strategic planning, team coordination, and process optimization. I collaborate with cross-functional teams to drive project success while developing leadership skills and a deep understanding of business operations.

Education

National Institute of Technology Rourkela

Bachelor of Technology - BTech, Biomedical/Medical Engineering, National Institute of Technology