Rohit Mukherjee.
Final-year CS student
Final-year CS student with hands-on experience in AI, NLP, LLMs, and scalable application development. Built and deployed ML models, real-time systems, and API-driven applications across healthcare and energy domains. Strong in Python, ML engineering, Generative AI, RAG pipelines, and cloud platforms.
Work Experience
Backend Engineering Intern
Zilios
Engineered scalable Go microservices with PostgreSQL, implementing idempotency keys to ensure reliable document generation for 100+ concurrent requests. Integrated Gemini and Vennix LLMs into backend REST APIs to automate code generation workflows, reducing manual processing time by 60%. Developed automated testing suites for cross-service API validation, catching critical database schema mismatches and improving deployment reliability.
AI Intern (Life Atlas Assistant Project)
Winniio AB
Built a RAG-based retrieval system boosting search accuracy by 27% and cutting query response time by 35% on live healthcare data. Refactored backend pipelines to improve system reliability by 40%, eliminating downtime during live patient interactions. Deployed a HIPAA-compliant GPT assistant on AWS, achieving 99% uptime and cutting patient query resolution time by 30%.
Skills
Projects
Energy Forecasting Model
Trained an LSTM model achieving ~92% prediction accuracy on real-world energy consumption data. Fine-tuned hyperparameters to boost model performance by 18% and cut inference time by 35%. Exposed model via Django REST APIs, supporting real-time predictions at 500+ requests/day.
AlphaFeed AI
Built a RAG pipeline over SEC 10-K filings using FinBERT + ChromaDB, achieving 98.2% recall with sliding window chunking to handle long-document context limits. Optimised OCR preprocessing with Tesseract v5 and OpenCV (Gaussian blur), improving character recognition accuracy by 14% (81.5% → 95.5%) on scanned PDFs. Integrated Mistral 7B via Groq LPU for sub-500ms market reasoning, delivering citation-traced risk assessments with zero hallucinations on financial figures.
AI Body Composition Analyzer
Trained an LSTM model for body composition analysis, outperforming the baseline by 24% in prediction accuracy. Engineered BLE data streaming pipeline handling 100+ real-time device readings/day with low latency. Designed an AI recommendation engine achieving 70%+ user acceptance rate in testing.
Education
Bachelor of Technology in Computer Science
Amity University
CGPA - 7.58
Senior Secondary Education
Delhi Public School
81.6%
Secondary Education
Delhi Public School
92.6%