I'm a final-year B.Tech student in Computer Science Engineering (AI & Analytics) at MIT School of Computing, Pune with a CGPA of 8.10/10 — and a track record of shipping real Python systems, not just side projects. My work spans real-time financial NLP pipelines, automated trading dashboards, intelligent email tools, and enterprise content platforms, built with Django, FastAPI, Redis, PostgreSQL, and a healthy obsession with clean architecture.
I've published peer-reviewed research at IEEE ESCI 2026 and IJSRA 2025 — systems I actually built and benchmarked, not theoretical exercises. On the ML side I've worked with HuggingFace Transformers, FinBERT, spaCy, and VADER across production NLP applications. I've also participated in Smart India Hackathon 2024 and earned certifications from AWS, IBM, and Certiport.
I combine strong backend engineering with AI/ML depth — comfortable across the full stack from PostgreSQL and Redis at the data layer, through Django and FastAPI in the middle, to Angular on the frontend. I'm fluent in Python, JavaScript, TypeScript, and C++, and have shipped production systems using Docker, Celery, WebSockets, Google APIs, and RabbitMQ.
Currently freelancing and actively looking for my next full-time role in backend engineering or AI/ML. Immediate joiner, comfortable with US/UK overlap hours. When I'm not coding, I'm probably writing about it on Medium.
Architect and deliver scalable Django/FastAPI backends for finance and enterprise clients. Work spans Redis pub/sub caching, PostgreSQL high-frequency logging, JWT auth, role-based access control, async task queuing via Celery, and RESTful API design. Build and ship automated data pipelines and analytics dashboards processing live third-party API feeds.
Designed, built, and published two peer-reviewed AI systems — FINSPIRE (real-time financial NLP, IEEE ESCI 2026) and MailGlance (AI email summarisation, IJSRA 2025). Full research lifecycle from architecture and implementation to empirical evaluation and international publication.
CGPA 8.10/10. Specialising in machine learning, NLP, data analytics, cloud computing, and full-stack development. Smart India Hackathon 2024 participant. Earned AWS Cloud Foundations, IBM Predictive ML, and Certiport Data Analytics certifications.
Python pipeline ingesting live RSS and API feeds with dual-engine NLP sentiment analysis — VADER + FinBERT. NumPy/Pandas signal aggregation over a Django + PostgreSQL backend achieving sub-second query response for actionable market signals.
NLP pipeline using HuggingFace Transformers + FastAPI connecting to Gmail via Google API. Semantic ranking via NumPy embedding arithmetic; inference optimised with model quantisation and batch processing to cut email overload.
ML-driven recommendation engine using NLP and collaborative filtering on user-supplied ingredients and dietary preferences. FastAPI backend with PostgreSQL and Redis caching for fast personalised lookups.
A Python pipeline for ingesting live financial news feeds and performing dual-engine sentiment analysis with VADER and FinBERT. Demonstrates sub-second actionable market signal delivery via a Django + PostgreSQL backend. Covers system architecture, empirical evaluation, and performance benchmarking at scale.
Proposes an NLP-based solution to workplace email overload using semantic understanding and transformer-based text summarisation. Demonstrates measurable improvements in information prioritisation and professional communication efficiency through empirical results and user feedback.