Headline

AIML Engineer @ IndiaNIC Infotech Limited – RAG, BERT & FastAPI | Cut API Latency 30% | Automates 80% Content Workflows

About

Hi, I’m Jainam Shah, an early-career data scientist and AI engineer working on production-grade machine learning systems with a focus on LLM applications, recommendation systems, NLP, and scalable backend optimization. Currently, I work as an AI/ML Engineer Trainee at IndiaNIC Infotech, where I contribute to real-world AI products by building recommendation engines, automating multimodal content enrichment pipelines, and optimizing high-concurrency ML-backed systems. My work has improved ranking relevance by 40%, automated 80% of listing enrichment workflows, and reduced API latency by 30%. I enjoy solving business problems using data, machine learning, and experimentation. My experience spans: • Recommendation Systems (Content-based & Hybrid) • Generative AI & RAG Pipelines • NLP & Transformer Models (BERT, DistilBERT) • Data Pipelines & ETL Workflows • Statistical Analysis & A/B Testing • FastAPI, SQL, Docker, AWS • Dashboarding & Business Analytics with Power BI Some projects I’ve built include: 🔹 AI-powered Recipe Recommendation System using RAG + FastAPI 🔹 Spotify Mood-Aware Recommendation System with hybrid ranking models 🔹 Amazon Supply Chain Analytics Dashboard using statistical analysis and forecasting I’m actively seeking 2026 opportunities in: • Data Science • Applied AI • Machine Learning Engineering • Recommendation Systems • Generative AI / LLM Engineering I’m especially interested in building intelligent systems that combine machine learning, data engineering, and real-world product impact. 📩 Open to entry-level roles and collaborations in AI/data science.

Location

Ahmedabad

Work experience

AI/ML Engineer Trainee at IndiaNIC Infotech Limited, Jan 2026 - Present · 5 mos, Ahmedabad, Gujarat, India, 🎯 Information Retrieval & Ranking: Architected a multi-stage hybrid ranking engine using TF-IDF and Cosine Similarity; engineered a weighted multi-signal scoring system (user behavior + semantic intent) that improved Mean Reciprocal Rank (MRR) by 40% across 10K+ listings. 👁️ Multimodal AI & Vision: Developed a high-throughput computer vision pipeline utilizing OpenAI GPT-4o and perceptual hashing for automated amenity detection; achieved 80% automation in content enrichment and a 15% boost in organic SEO. ⚡ System Latency Optimization: Refactored high-concurrency Django/PostgreSQL backends; implemented Redis-based caching and optimized ORM indexing, reducing P99 API latency by 30% for complex geospatial queries. 🤖 LLM Orchestration: Deployed a production-grade Generative AI pipeline (GPT-3.5) with a deterministic fallback architecture for automated property descriptions, ensuring 100% uptime and high-fidelity output. ⚙️ Distributed Data Engineering: Designed asynchronous ETL workflows using Celery and RabbitMQ to process real-time market pricing intelligence and implemented schema validation protocols ensuring 99.9% data integrity. 💬 Real-time Event Streaming: Engineered a stateful bi-directional messaging layer using Django Channels (WebSockets) and Redis Pub/Sub, supporting thousands of concurrent real-time connections.

Education

Master of Science - MS, Information Technology, Gujarat University

Bachelor of Science, Information Technology, Gujarat University