Sanatan Kafle - Portfolio

Who I Am

About Me

I'm a Computer Engineer with a deep passion for Data Science and Web Development. I enjoy creating websites with aesthetic designs and seamless functionality. Another part of me loves working with data, exploring patterns, and watching them come alive through the magic of Machine Learning models.

Machine Learning, AI, and LLMs keep me constantly engaged and excited. I believe in continuous learning and pushing the boundaries of what's possible with technology.

2+

Years Experience

15+

Projects Completed

5+

Technologies

Download Resume

What I Know

Skills & Expertise

Python

ML, Data Analysis, Backend

Machine Learning

Neural Networks, CV, NLP

AWS

Cloud Deployment & MLOps

Django

Full-Stack Web Development

SQL

Database Management

JavaScript

Frontend Development

C++

DSA & System Programming

Git

Version Control

MLOps

ML Pipeline & Deployment

Career Journey

Work Experience

Sep 2024 - Present

Machine Learning Engineer

Shrig Solutions, Kathmandu

Deep Learning: Designed and trained advanced vision models for object detection, segmentation, classification, depth estimation.
AR and 3D analytics: Engineered 3D length estimation algorithms leveraging LiDAR data and AR technologies
MLops: Streamlined end-to-end ML workflow by building automated data ingestion, training, and deployment pipeline using AWS, MLflow, Grafana
Cloud & API Integration: Deployed Machine Learning architectures on AWS and developed backend REST APIs using FastAPI to serve model inference to production through microservices
Research and Development: Researched and implemented projects like video inpainting, Duplicate Image Detections, Vision Transformers.
Mentorship and Training: Trained and mentored multiple trainee and interns on machine learning concepts.

Jun 2024 - Sep 2024

Machine Learning Intern

Shrig Solutions, Kathmandu

Computer Vision Development: Developed and fine-tuned YOLO-based architectures for object detection, pose estimation, and instance segmentation, alongside monocular depth estimation models.
Data Engineering & Automation: Engineered automated scripts for keypoint annotation workflows within CVAT, significantly reducing manual data labeling time and accelerating model training cycles.
Applied Machine Learning: Translated core machine learning concepts into practical implementations, directly contributing to the foundational development and testing of early-stage computer vision pipelines.

Academic Background