// résumé · 2025

Abhishek
Shah

AI/ML Engineer & Technical Project Manager
Open to Opportunities
4+ Years Experience
ML Engineer · Technical PM
Nepal · Remote Preferred
Profile

AI/ML Engineer and Technical Project Manager with 4+ years building production systems in Machine Learning, LLMs, Recommender Systems, and cloud-native AI infrastructure. Former AI Team Lead at Inflancer Technology; now building independently across AI, tooling, and open-source. Ranked #61 among Nepal's top open-source contributors on GitHub. Actively seeking ML Engineer or Technical PM roles.

Experience
AI Engineer & AI Team Lead
Inflancer Technology — Kathmandu, Nepal
Apr 2024 – Dec 2025
  • Architected and deployed production Recommender Systems on Docker and Kubernetes, directly improving content personalisation and user engagement at scale.
  • Built NLP embedding-based semantic search to replace keyword lookups with intent-aware, contextually relevant content discovery.
  • Designed scalable AI microservices integrating Kafka for real-time data pipelines and event-driven processing on cloud infrastructure.
  • Led cross-functional AI collaboration across product, engineering, and business — translating model capabilities into measurable outcomes.
Project Manager
Inflancer Technology — Kathmandu, Nepal
Oct 2024 – Dec 2025
  • Drove end-to-end delivery of AI and product initiatives using Agile methodologies, owning sprint planning, risk mitigation, and stakeholder alignment.
  • Coordinated cross-functional teams to maintain on-time, high-quality releases with clear communication up to leadership.
ML Engineer & Research Contributor
Freelance / ResearchGrad — Nepal
Jan 2019 – 2024
  • Fine-tuned a Llama-2 7B model on a custom code-description dataset, shipping a fully functional Python code generator.
  • Built a real-time hand gesture recognition system with CNNs and OpenCV, deployed live via Vercel.
  • Contributed to ML research on Nepali Music Genre Classification and Multi-modal Hate Speech Detection, supporting a mentor's M.Sc. thesis.
ML Intern
Codsoft — Bangalore, India
Oct – Nov 2023
  • Built credit card fraud detection and customer churn prediction models; achieved 86.55% accuracy with Random Forest, SMOTE, and hyperparameter tuning.
  • Delivered an SVM spam classifier at 98% accuracy and an NLP movie genre classifier with a production-ready interface.
ML Mentor
ACES Bootcamp — Dharan, Nepal
Feb 2024
  • Mentored students through ML fundamentals, live debugging, and model improvement during a week-long intensive training camp.
Projects
TitanML ↗ Live

Zero-dependency, physics-powered AI knowledge graph engine with interactive bubble-graph visualization. Explores AI concept relationships dynamically — no external libraries required.

Test Maker Engine ↗ Live

Zero-backend quiz engine — pure HTML/CSS/JS/JSON. 50 randomised questions, keyboard nav, dark/light mode, session resume, rich results breakdown. Fully open-source for educators.

CodeBeing ↗ Live

Natural language-to-Python code generator powered by a fine-tuned Llama-2 7B model. Built with ReactJS and deployed on Vercel.

Sentiment Analyzer ↗ GitHub

NLP sentiment classification using DistilBERT, achieving 89% accuracy on benchmark datasets.

Hand Gesture Recognizer ↗ GitHub

CNN + OpenCV pipeline for real-time gesture-to-sign-language translation. Built for accessibility applications.

Flappy Bird: God Mode ↗ Live

AI-augmented variant with adaptive difficulty and enhanced game mechanics — built to explore algorithmic game logic and agent-driven behaviour.

Education
Bachelor of Computer Engineering
IOE, ERC — Tribhuvan University, Nepal
Data Mining OOP & Design Artificial Intelligence Theory of Computation
Class of 2019
Community & Leadership
  • #61 in Nepal – Top GitHub Committers: Ranked among Nepal's most active open-source contributors on the global top.committers leaderboard.
  • Tech Writer on Medium: Weekly articles on LLMs, AI engineering, and software tools — reaching 1K+ readers/week. Profile ↗
  • Industry Case Studies: Independently researching how AI-driven companies (Spotify, Netflix, Airbnb) architect and monetize their ML systems — insights applied to engineering and product decisions.
  • Open-Source Education: Maintains The Coder's Handbook, how-I-learned-python, and how-I-learned-ml as structured beginner guides.
  • Deltathon Organizer: Managed logistics and coordination for the ACES major hackathon; later competed as Team ZAV.