Subash Pandey
AI/ML Engineer · GenAI Developer · Data Scientist
AI/ML engineer from Nepal with a strong interest in Generative AI and applied machine learning. I hold an MSc in Data Science from the University of Exeter (Merit) and a BSc (Hons) in Computing from London Metropolitan University (2:1).
I build and maintain AI-driven features — from conversational AI to GenAI chatbots with RAG pipelines, LLM evaluation frameworks, and audio feature extraction. I led the development of a GenAI chatbot integrated with CRM using LangGraph, RAG pipelines, and Qdrant for intent detection, contextual retrieval, and analytics tracking.
I take pride in writing clean code, thinking deeply about problems, and building meaningful, responsible AI solutions that create real impact.
Experience
Scopic Software LLC
scopicsoftware.comKathmandu, Nepal (Remote)
Remote AI/ML Engineer
Oct 2024 – Present · Python · LangGraph · FastAPI · AWS · Docker
Conversational AI platform, GenAI chatbot with LangGraph + RAG + Qdrant, LLM evaluation pipelines, audio feature extraction R&D, SEO SaaS platform as full-stack developer.
Peace Nepal Dot Com
peacenepal.comKathmandu, Nepal
AI/ML Engineer
Jul 2024 - Nov 2024 · RAG · Multi-agent · LLM Fine-tuning
Chatbots for Banking, Travel & Customer Support with RAG and multi-agent frameworks. Deployed interactive web chat applications.
Icebrkr AI Solutions
AI/ML Engineer
Mar 2024 - Jun 2024 · HuggingFace · PyTorch · AWS
Scalable ML models for data analysis and automation. Deployed models for production in cloud environments.
Contentio Lab Pvt. Ltd.
Kathmandu, Nepal
Data Analyst
Aug 2021 - Apr 2022 · Python · Pandas · SQL
Data pipelines, visualisation with Matplotlib/Seaborn, customer segmentation — 20% reduction in processing time.
iMark Private Limited
Kathmandu, Nepal
Frontend Intern
Oct 2020 - Jan 2021 · React · Node.js · REST API
React.js to-do application with CRUD backend and user authentication.
Budhanilkantha Education Services
Kathmandu, Nepal
Tutor
Oct 2018 - Apr 2019
A-Level Computer Science tutoring and personalised lesson plans.
Projects
Activity Recognition
ML / SensorsClassified human physical activities (walking, jogging, sitting, typing, etc.) using XGBoost on accelerometer and gyroscope data from smartphones and watches. Hyperparameter tuning via random search achieved >85% accuracy.
Steam Video Game ML
Network AnalysisExplored the evolution of game genres on Steam using network analysis. Identified emergent sub-genres, influential genre nodes, and key drivers of player engagement including ratings, achievements, and pricing models.
Wikipedia Adminship
Network AnalysisInvestigated social network dynamics within Wikipedia's administrator election process. Calculated centrality measures, performed community detection via hierarchical clustering, and analyzed voting blocs.
Stock Variables Analysis
Data ScienceExploratory data analysis of stock prices across exchanges. Identified significant variables affecting closing prices through correlation analysis, regression, feature selection, and data clustering.
Floki eCommerce
Full-StackFull-stack e-commerce application built with the MERN stack. Features include product browsing, searching, filtering, cart management, user authentication, order processing, and payment integration with Redux state management.
Certifications
Great Learning
Education
University of Exeter
Master of Science in Data Science (2022 - 2023)
Statistics, Machine Learning, Social Network Analysis, Data Science Applications. Thesis: Machine Learning the Steam Video Game Database. Grade: Merit.
London Metropolitan University
BSc (Hons) Computing (2019 - 2021)
Computer Science Fundamentals, Software Engineering, Databases, Networking, Cloud Computing. Thesis: Floki, An eCommerce Web Application. Grade: 2:1.
Publications
Machine Learning the Steam Video Game Database
University of Exeter · 2023
Explored the evolution of game genres on Steam using network analysis and machine learning. MSc thesis.
Wikipedia Adminship Network Analysis
University of Exeter · 2023
Investigated social network dynamics within Wikipedia's administrator election process using centrality measures and community detection.
Recommendations
"I had the opportunity to work with Subash as an AI consultant on an early-stage AI project, and his expertise was invaluable. He helped my team and me navigate our initial AI strategy, clarify our approach, and identify the right areas to prioritize. His ability to break down complex concepts into actionable steps made the process smooth and insightful. I'd recommend him to anyone looking for guidance on ML/AI strategy or implementation!"
