Headline

AI/ML Engineer at Feathersoft | ML Pipelines • Graph-Based AI • Deep Learning • Generative AI

About

Passionate AI/ML Engineer with a strong foundation in Deep Learning, Graph-based AI, and Generative AI systems. Currently building intelligent, scalable machine learning solutions at Feathersoft (ThinkBio.Ai), where I work on graph-driven data modeling, embeddings, and ML pipelines to solve complex, data-intensive problems in biological and healthcare domains. Driven by curiosity and hands-on engineering, I enjoy designing end-to-end AI systems — from data preprocessing and feature extraction to model development and deployment. I’m particularly interested in GraphRAG architectures, vector databases, and applied deep learning, and how they can be used to transform life-science data into actionable insights. Always eager to learn, collaborate, and push the boundaries of practical, real-world AI systems.

Location

Kochi

AI stack

claude

codex

mcp

openai

Google ADK

Work experience

AI ML Engineer at Feathersoft, Oct 2025 - Present · 1 yr 1 mo, Ernakulam, Kerala, India, Worked on designing and developing graph-driven AI/ML systems for biological and healthcare applications, focusing on transforming complex, structured data into intelligent, queryable, and scalable AI solutions. Core Contributions & Responsibilities Built AI/ML solutions using Knowledge Graphs to model complex domain relationships, improving data semantics, contextual understanding, and downstream intelligence. Designed and implemented graph data models in Neo4j, including nodes, relationships, properties, and constraints for large, interconnected datasets. Developed graph-based retrieval and intelligence pipelines, enabling structured reasoning and efficient querying over domain knowledge. Worked on GraphRAG-style architectures, embedding graph entities (nodes, relationships, and properties) to support similarity search and semantic retrieval. Integrated vector embeddings with graph databases, enabling hybrid graph + vector intelligence for AI-driven applications. Used Apache Jena to work with RDF, ontologies, and semantic web concepts, supporting ontology-driven data modeling and semantic optimization. Assisted in building end-to-end ML pipelines, including data preprocessing, feature extraction, model integration, and inference workflows. Applied Deep Learning concepts to real-world datasets, focusing on practical implementation rather than theoretical research. Collaborated closely with cross-functional teams to translate biological and healthcare domain requirements into scalable AI system designs. Contributed to experimentation with Generative AI systems at the architecture level, focusing on retrieval, embeddings, and system integration rather than model fine-tuning. Optimized graph queries and data structures to improve performance, scalability, and reliability of AI-powered systems. Participated in ideation and execution of early-stage AI initiatives in a fast-paced startup environment, taking ownership of technical components.

AI ML Intern at Feathersoft, Jul 2025 - Oct 2025 · 4 mos, Ernakulam, Kerala, India, AI/ML Intern

Summer Intern at Jio, Jul 2024 - Jul 2024 · 1 mo, Bengaluru, Karnataka, India

Education

Bachelor of Technology - BTech, Electronics and Communications Engineering, Rajagiri School of Engineering & Technology

High School, Mathematics and Computer Science, Naipunnya Public School - India

Public links

alby-rajesh.vercel.app: https://alby-rajesh.vercel.app/