Open to opportunities

Pranil Parajuli

@pranilparajuli

AI/ML Engineer and computer vision researcher building real-time deep learning systems, RAG pipelines, and generative AI experiences.

Nepal

Message

What I'm looking for

I’m looking for a role where I can build and deploy real deep learning systems—computer vision, RAG/LLM applications, and generative AI—on Linux-first workflows, with a focus on measurable quality, reliability, and practical impact.

I’m a Computer Engineering graduate with hands-on industry experience in deep learning, computer vision, and generative AI. In my recent role as an AI/ML Engineer, I developed a real-time face recognition system using MTCNN and FaceNet (PyTorch, OpenCV), improving reliable identity verification under varied lighting.

I also implemented skin analysis and wrinkle detection, contributed to a live social impact platform, and performed QSAR research with ML regression models. I’m especially excited by end-to-end deployment: I’ve optimized and benchmarked ML inference pipelines on Linux, and I build RAG and generative AI systems end-to-end through projects like RAG grounding with LangChain and local LLM backends, plus ControlNet + Stable Diffusion smart-city generation.

Experience

Work history, roles, and key accomplishments

AI/ML Engineer

Acaiberry Technologies

Nov 2025 - Mar 2026 (4 months)

Developed a real-time face recognition system using MTCNN and FaceNet in PyTorch/OpenCV for robust identity verification under varied lighting, and built skin analysis and wrinkle detection models. Optimized ML inference pipelines on Linux for deployment in resource-constrained environments and supported QSAR regression research and a live social impact platform (myabhiyan.com).

FaceNet PyTorch OpenCV Computer Vision regression Inference Optimization Linux PostgreSQL

Education

Degrees, certifications, and relevant coursework

Thapathali Campus

Bachelor of Computer Engineering, Computer Engineering

Grade: Aggregate: ∼80% (8th semester)

Bachelor of Computer Engineering; completed in Spring 2026. Coursework covered machine learning, computer vision, data structures & algorithms, databases, operating systems, computer networks, and digital signal processing.