AI Research Engineer with less than a year in Generative AI & Machine Learning
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Assessing your cultural and operational fit
AI Engineer and M.Sc Data Science postgraduate (90%) with hands-on experience building Generative AI systems, multimodal RAG pipelines, and multilingual NLP applications. Skilled in LLM API integration, vector databases, semantic search, and knowledge graph construction. Proven ability to deliver end-to-end AI solutions from ideation to Streamlit deployment.
Bishop Heber College
M.Sc Data Science · Data Science
August 1, 2024 – June 30, 2026
St. Joseph's Autonomous College
B.Sc Mathematics · Mathematics
August 1, 2021 – June 30, 2024
NewDreams Technology
AI Research Intern
December 1, 2025 – February 1, 2026
Tiruchirappalli, Tamil Nadu, India
Afame Technology
Data Analyst Intern
December 1, 2024 – January 1, 2025
Bengaluru, Karnataka, India
Smart Talent Acquisition System
June 25, 2026 – Present
Developed NLP-powered resume screening system matching candidates to job descriptions via TF-IDF and embedding-based ranking across 3 role archetypes. Built end-to-end ML pipeline (PDF parsing → preprocessing → similarity scoring) and deployed an interactive recruiter dashboard via Streamlit with ranked match scores.
View ProjectAI Story-to-Logic Converter
June 25, 2026 – Present
Built a multilingual AI pipeline converting Tamil/English audio (MP3/WAV) into structured predicate logic and Prolog facts using OpenAI Whisper (ASR) and spaCy (NLP event extraction). Constructed dynamic knowledge graphs from story events using NetworkX with real-time Streamlit visualization; implemented Tamil language detection enabling bilingual logic output.
View ProjectReal-Time Employee Monitoring System
June 25, 2026 – Present
Built real-time distraction detection using MediaPipe Face Mesh and OpenCV, achieving 94% gaze-tracking accuracy at 25 FPS; generated automated productivity heatmap reports.
Cultural Fit Analysis
The candidate's academic projects and internship experiences demonstrate a strong interest in cutting-edge AI technologies, aligning well with a research-oriented role. The diversity of projects (talent acquisition, story conversion, employee monitoring) indicates a willingness to explore different applications of AI. The mention of hackathon participation suggests a collaborative and competitive spirit. However, the limited professional experience might require mentorship in a fast-paced industry environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and an ability to deliver functional prototypes. The academic background in Data Science and Mathematics provides a strong analytical foundation. The internship experience, though limited in duration, shows practical application of AI concepts in a professional setting. The candidate's ability to work on diverse projects (NLP, CV, Multimodal AI) suggests adaptability and a broad interest in AI domains.