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AI Engineer with 1+ years in Machine Learning & FastAPI Development
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML Engineer skilled in developing machine learning models, preparing high-quality datasets, and deploying scalable inference APIs. Experienced in Python, data preprocessing, model evaluation, and designing FastAPI services optimized for performance and reliability. Passionate about building practical, production-focused AI solutions.
LJ University, Ahmedabad
Master of Computer Applications (MCA)
August 1, 2023 – April 1, 2025
Som-Lalit Institute of Computer Applications, Ahmedabad
Bachelor of Computer Applications (BCA)
June 1, 2020 – June 1, 2023
AI Tech Partner
AI/ML Engineer
April 1, 2025 – Present
India
AI-Powered Business Travel Planner
June 29, 2026 – Present
Developed an intelligent travel planning system generating personalized business trip itineraries using Large Language Models (Google Gemini) integrated with real-time travel APIs (Amadeus, IRCTC). Implemented vector search using Pinecone and Sentence Transformers for semantic activity matching, enabling conversational itinerary refinement with 95%+ accuracy. Built full-stack application with FastAPI backend and React frontend, incorporating user authentication (Supabase), budget management, and dynamic scheduling around business meetings. Designed robust API integration layer with graceful fallback mechanisms, handling 3+ external APIs with async processing and comprehensive error handling. Engineered feedback processing system using natural language parsing and vector similarity search to identify and regenerate specific itinerary activities based on user requests.
AI-Powered Time & Attendance Management System (TMS) Analytics
June 29, 2026 – Present
Developed an enterprise ML platform for workforce analytics featuring fraud detection, absenteeism forecasting, and overtime prediction with 85%+ accuracy across 100,000+ attendance records. Engineered a fraud-detection system using ensemble methods (Random Forest, XGBoost, Isolation Forest) to identify buddy-punching, time theft, and device anomalies with real-time alerting capabilities. Built a production FastAPI REST API with 25+ endpoints, automated model-retraining pipelines, and seamless integration with an ASP.NET Core enterprise application. Implemented advanced feature-engineering including temporal patterns, behavioral profiling, and multi-dimensional risk scoring for comprehensive workforce analytics. Designed a scalable ML pipeline with automated preprocessing, StandardScaler normalization, model persistence, and robust handling of production edge cases. Created predictive models for 7-day/30-day absenteeism forecasting, late/early arrival prediction, and overtime estimation to support proactive workforce planning.
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with an AI Engineer role, focusing on practical applications of machine learning and deep learning. The diversity in projects, from travel planning with LLMs to workforce analytics with traditional ML, shows adaptability and a broad interest in applying AI to different domains. The use of modern tools and frameworks (FastAPI, React, Docker, Google Gemini, Pinecone) indicates a proactive approach to learning and adopting new technologies, which is a good cultural fit for innovative tech environments.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving orientation and a focus on building production-ready, scalable AI solutions. The emphasis on robust API integration, error handling, and performance optimization suggests a practical and detail-oriented approach. The experience with full-stack development (FastAPI, React) and integration with enterprise applications (ASP.NET Core) points to an ability to work across different layers of a system and collaborate effectively.