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AI Engineer with less than a year in machine learning & NLP solutions
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with hands-on experience building end-to-end machine learning and NLP solutions, from data preprocessing and feature engineering to model training, evaluation, and deployment. Designed and deployed a full-stack GenAI platform with RAG-based document grounding, confidence scoring, and multi-agent orchestration. Strong foundation in Python, SQL, and statistical analysis, with proven ability to translate business problems into scalable AI/ML solutions on AWS, Azure and GCP.
Government Women Engineering College, Ajmer
Bachelor of Technology · Artificial Intelligence & Machine Learning
August 1, 2021 – June 30, 2025
Drona Pay
Data Engineer Intern
August 1, 2025 – January 31, 2026
India
IBM SkillsBuild
Data Analysis Intern
June 1, 2024 – August 31, 2024
India
VaultAI — Personal Finance Intelligence System
June 24, 2026 – Present
Built a production-grade full-stack GenAI platform using FastAPI, Next.js, PostgreSQL, JWT, Pydantic, deployed on Vercel & Hugging Face. Developed a RAG pipeline (Qdrant, Sentence Transformers, Groq LLM) with user-isolated retrieval, caching, and reproducible outputs. Engineered a validation-driven analytics system with confidence scoring and guardrails to reduce LLM hallucinations. Designed a LangGraph multi-agent system with deterministic financial simulations and optimization logic.
View ProjectDatalake Optimization
June 24, 2026 – Present
Built dynamic Apache Airflow DAGs for multi-tenant ETL on Iceberg tables (refined zone). Optimized Trino queries using partition and bucket-aware strategies. Automated snapshot and orphan file cleanup, reducing data lake storage by 50%. Added SQL-based validations, alerts, and tests for reliable, production-ready pipelines.
Facial Emotion Recognition using OpenCV and Keras
June 24, 2026 – Present
Built a real-time facial emotion detection model using CNNs. Processed video frames to detect and classify emotions instantly.
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in cutting-edge AI technologies (GenAI, RAG, multi-agent systems) and practical application, aligning well with an innovative AI engineering culture. The diversity of projects, from finance intelligence to data lake optimization and emotion recognition, shows a broad technical curiosity. However, the experience is primarily academic and internship-based, which might require mentorship in a fast-paced, senior-level production environment.
Soft Skills & Operational Fit
The candidate's profile and project descriptions indicate a proactive and problem-solving attitude, particularly in optimizing systems and building end-to-end solutions. The psychometric test score suggests a moderate level of logical reasoning and work attitude, with potential areas for growth in stress handling and team collaboration. The English test score indicates good communication clarity.