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Software Engineer with 1+ years in AI/ML & Fullstack Development
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Assessing your cultural and operational fit
Highly motivated Software Engineer with 1.3 years of experience in developing robust applications using Java, Spring Boot, React.js, and Node.js. Skilled in AI/ML, NLP, and Generative AI, with a proven track record of delivering end-to-end projects such as AI pipelines for multilingual transcription and heart disease risk predictors. Experienced in microservice architecture, API development, data validation, and achieving high test coverage to ensure production-grade software quality.
Siksha 'O' Anusandhan Deemed to be University
B.Tech · Computer Science Engineering
August 1, 2021 – June 30, 2025
DAV Public School, Pokhariput
Senior Secondary Education
N/A – May 31, 2021
Kendriya Vidyalaya, Paradip Port
Secondary Education
N/A – May 31, 2019
Hewlett Packard Enterprise
Software Engineering Virtual Experience Program on Forage
March 1, 2026 – Present
India
MediaMint
Associate I
March 1, 2025 – December 31, 2025
Bhubaneshwar, Odisha, India
NuanceAI: Video & Meeting Intelligence
May 1, 2026 – June 30, 2026
Engineered an end-to-end AI pipeline processing audio/video files through Groq Whisper API (English) and Sarvam AI (Hinglish), achieving multilingual transcription with zero local model dependencies on cloud infrastructure. Architected a production-grade RAG system using LangChain LCEL, ChromaDB vector store, and HuggingFace sentence embeddings; enabling context-aware semantic Q&A over full video transcripts powered by Mistral AI. Deployed the application using Streamlit auto-generating structured meeting intelligence - Summary, Action Items, Key Decisions, and Open Questions across 7+ file formats with chunked audio processing and one-click export. Diagnosed and resolved a critical cloud deployment failure caused by YouTube's IP-level datacenter blocking; re-architected the ingestion pipeline from yt-dlp to a Groq API-first, file-upload model restoring full production functionality.
View ProjectCardioAI: Heart Disease Risk Predictor
March 1, 2026 – June 30, 2026
Engineered an end-to-end machine learning pipeline for cardiovascular risk prediction; automated data preprocessing, feature engineering, and model training on 918 clinical records using Python and Scikit-learn. Benchmarked 5 classification algorithms (KNN, SVM, Logistic Regression, Naive Bayes, Decision Tree); selected KNN via data-driven evaluation achieving 88.6% accuracy and 90% F1 score, optimizing for clinical risk detection. Deployed a clinical decision-support tool on Streamlit Cloud with real-time probability-based risk scoring, interactive Plotly dashboards, and StandardScaler normalization for reproducible inference.
View ProjectMuse: A Music Streaming Platform
January 1, 2026 – June 30, 2026
Built and deployed a full-stack music streaming platform using React.js, Node.js, Express.js, and MongoDB Atlas with 5 RESTful APIs, role-based access control, frontend on Vercel and backend on Render. Implemented JWT authentication via HTTP-only cookies, bcryptjs password hashing, and custom Express middleware; load tested at 279ms median response and 100% success rate across 300 requests. Designed MongoDB schemas with Mongoose populate() for relational lazy loading; integrated ImageKit CDN and Multer for stateless audio file storage. Architected MVC codebase with strict separation of routes, controllers, models, middleware, and services, shipped to production with zero downtime.
View ProjectCultural Fit Analysis
The candidate's project portfolio showcases a strong inclination towards innovative and complex technical challenges, particularly in AI/ML and full-stack development. The personal projects demonstrate initiative and self-driven learning, which aligns well with a culture that values continuous improvement and independent problem-solving. The experience with a virtual internship at HPE suggests an understanding of corporate environments. However, the lack of team-based project descriptions or explicit mentions of collaboration limits the depth of cultural fit assessment. The 'Associate I' role at MediaMint, while providing professional experience, is less technically aligned with a Software Engineer role, which might indicate a broader career exploration rather than a focused path.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving, particularly in diagnosing and resolving a critical cloud deployment failure. The emphasis on achieving high test coverage (85%+) and ensuring production-grade quality suggests an attention to detail and commitment to robust solutions. The diverse range of projects, from AI/ML to full-stack development, implies adaptability and a willingness to tackle different technical challenges. However, without direct interview data, assessing collaboration, stress handling, and communication clarity in a team setting is limited.