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AI Engineer with 1+ years in Machine Learning & Bioinformatics
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AI/ML Engineer and Bioinformatics Researcher with an M.Tech in Computer Science (Data Science AI), underpinned by a strong foundation in M.Sc. Physics. Experienced in statistical analysis pipeline development, omics and clinical data integration, and biomarker discovery, with a peer-reviewed publication in network-based bioinformatics. Proficient in R, Python, deep learning, LLM fine-tuning, and RAG systems, with hands-on experience delivering production-grade AI solutions at Expeed Software. Bridges rigorous scientific reasoning with practical data-driven solutions across healthcare AI and life science domains.
Cochin University of Science and Technology
M.Tech · Computer Science with specialisation in Data Science and Artificial Intelligence
August 1, 2023 – June 30, 2025
University of Calicut
M.Sc. · Physics
August 1, 2020 – June 30, 2022
MES Kalladi College Mannarkkad
B.Sc. · Physics
August 1, 2017 – June 30, 2020
Expeed Software
Associate Software Engineer
May 1, 2025 – Present
India
NIT Calicut
Research Intern
August 1, 2024 – April 1, 2025
India
Multi-Agent Onboarding Automation System (SaaSLogic)
January 1, 2026 – June 1, 2026
Built a multi-agent automation system using LangGraph for end-to-end customer onboarding in a SaaS platform, handling subscription management, customer plan selection, and profile updates with minimal human intervention.
Domain-Specific LLM (DSLM) Fine-Tuning Framework
January 1, 2026 – June 1, 2026
Developed DSLMs using continuous pretraining and supervised fine-tuning (SFT) on domain-specific data for AI integration in low-code platforms like Apptor.
Domain-Specific LLM for Digital Marketing
January 1, 2025 – December 31, 2025
Fine-tuned LLMs to support content generation for marketing teams, enabling domain-adapted text generation for content writers.
AI-Based Lead Scoring (CRM)
January 1, 2025 – December 31, 2025
Developed ML and rule-based models to predict lead quality using behavioral and communication data.
Eye Disease Prediction from Fundus Images
January 1, 2025 – December 31, 2025
Built deep learning models (ResNet, CNNs) for detection of diabetic retinopathy, glaucoma, and cataract.
RAG-based Document Search System
January 1, 2025 – December 31, 2025
Built retrieval-augmented generation (RAG) system using vector embeddings for semantic search and context-aware responses.
Breast Cancer Genomic Analysis
January 1, 2024 – December 31, 2024
Performed differential gene expression and pathway enrichment analysis using TCGA data.
Multi-Omics Network Analysis for HNSCC
January 1, 2024 – December 31, 2024
Constructed multiplex networks and applied clustering and enrichment analysis to identify disease-associated modules.
Traffic Sign Recognition
January 1, 2023 – December 31, 2023
Developed image classification models using HOG features with SVM, KNN, and Random Forest.
UWB MIMO Antenna Design
January 1, 2022 – December 31, 2022
Designed and implemented a compact antenna system for efficient wireless communication.
One year Project Internship
NIT Calicut
January 1, 2024 – Present
Summer Internship
NIT Calicut
January 1, 2024 – Present
Five-day Workshop on the topic "Generative AI and Large Language Models”
Cochin University of Science and Technology
January 1, 2024 – Present
IBM Skill Build Internship Program
IBM
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, spanning SaaS automation, digital marketing, healthcare AI, and bioinformatics, demonstrates adaptability and a broad interest in applying AI across various domains. This breadth of experience, combined with academic achievements and research internships, suggests a proactive and continuous learning mindset, which aligns well with innovative and research-driven cultures. The focus on practical, production-grade AI solutions at Expeed Software indicates a results-oriented approach.
Soft Skills & Operational Fit
The candidate's resume highlights contributions to technical documentation, including research manuscripts and system design, suggesting good communication and organizational skills. Collaboration with cross-functional teams is also mentioned, indicating potential for teamwork. However, without specific behavioral assessment data, a deeper evaluation of soft skills and operational fit is limited.