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AI Engineer with 2+ years in ML solutions and Power Platform automation.
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Assessing your cultural and operational fit
Python developer with hands-on experience building end-to-end AI/ML solutions — from data pipelines and model training to production deployment. Proficient in scikit-learn, RAG pipelines, local LLM orchestration via Ollama, and FastAPI-based ML backends. Built and shipped three personal AI projects spanning recommendation systems (Random Forest), domain-specific RAG assistants (ChromaDB + semantic embeddings), and local coding agents. Concurrently holds ~1 year of enterprise experience delivering Power Platform and automation solutions. Eager to transition full-time into AI engineering and contribute to intelligent workflow automation.
Mar Baselious Institute of Technology and Science
B.Tech · Computer Science Engineering
August 1, 2020 – June 30, 2024
NEST Digital
Software Developer – Power Platform & Automation
July 1, 2024 – Present
Thiruvananthapuram, Kerala, India
Quest Innovative Solutions
Data Analyst Trainee
March 1, 2024 – July 1, 2024
Thiruvananthapuram, Kerala, India
Beats - Personal AI Music Recommendation Engine
June 1, 2026 – Present
Built a full-stack AI music PWA with a custom ML recommendation engine that learns listening patterns over time using a two-phase Random Forest model. Engineered end-to-end ML pipeline: data collection (yt-dlp), feature engineering on audio metadata, model training, evaluation, and real-time inference via FastAPI. Designed async SQLAlchemy schema (4 tables) for track storage, play history, and model feedback — demonstrating SQL/NoSQL-equivalent structured data management. Deployed frontend on Vercel and backend on Railway — full production deployment cycle from model to user-facing application.
YoctoGPT - Domain-Specific RAG CLI Assistant
June 1, 2026 – Present
Built a production RAG pipeline for Embedded Linux engineers, grounding LLM responses in official Yocto docs, Stack Overflow threads, and curated BitBake syntax datasets. Implemented semantic search with all-MiniLM-L6-v2 embeddings + ChromaDB vector store — directly applicable to retrieval-augmented LLM solutions. Integrated SQLite-backed session memory for persistent multi-turn conversations, demonstrating database integration with LLM workflows. Validated by an embedded Linux engineer as a domain expert — shipped as a usable tool, not just a prototype.
MARC - Local AI Coding Assistant
June 1, 2026 – Present
Built a fully local, privacy-first AI coding assistant running on Ollama — demonstrating hands-on experience running and fine-tuning local LLMs on constrained hardware. Engineered an LLM Intent Router classifying natural language into structured intents (CHAT, READ, EDIT, CREATE, LIST) enabling agentic code execution. Implemented sliding window memory with intelligent context truncation for resource-constrained local inference — showing practical MLOps-adjacent engineering.
Jobman – AI Job Application Agent
June 1, 2026 – Present
Built an autonomous agent that scrapes Naukri, LinkedIn, Indeed, and Remotive; scores jobs against resume via LLM; tailors resumes per JD; and sends Telegram notifications. Deployed on Railway — full production agentic pipeline integrating REST APIs, LLM calls, and automated workflows.
Accenture North America Virtual Internship
Accenture (Forage)
June 1, 2026 – Present
PL-900 (Microsoft Power Platform Fundamentals) certification
Microsoft
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse personal projects (AI Job Application Agent, Music Recommendation Engine, RAG CLI Assistant, Local AI Coding Assistant) showcase a strong passion for AI and a proactive approach to learning and applying new technologies. This aligns well with an innovative and growth-oriented culture. The experience in both AI/ML development and enterprise automation suggests adaptability and a broad skill set, which can be beneficial for cross-functional collaboration. However, the professional experience is relatively short, and the target role is AI Engineer, while current experience is in Power Platform, indicating a transition. This might require some cultural alignment to a pure AI engineering focus.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-driven individual capable of taking projects from conception to deployment. The experience in Power Platform suggests an understanding of business process automation and enterprise environments, which could translate to operational fit in roles requiring intelligent workflow automation. The personal projects demonstrate strong problem-solving and independent learning capabilities.