Pathum Dilhara

AI Engineer

https://www.opentalent.in/pathum-dilhara

AI Engineer with less than a year in Machine Learning & AI development

Key Strengths

Strong foundational knowledge in Machine Learning and Deep Learning, evidenced by academic projects.
Practical experience with various AI models including BERT, CNNs, Random Forest, and XGBoost.
Proficiency in building end-to-end AI applications, including backend (FastAPI) and mobile integration (Flutter).
Experience with LLM-based RAG pipelines and semantic search using ChromaDB and SentenceTransformers.
Demonstrated ability to work with diverse data tools like Pandas, NumPy, and DuckDB.
Clear interest in production-ready AI systems and scalable intelligent applications, aligning with an AI Engineer role.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project diversity, covering areas like finance, healthcare (disease detection), and recommendation systems, indicates a broad interest in applying AI across different domains. The focus on building 'production-ready AI systems' and 'real-world ML applications' aligns well with a results-oriented and innovative culture. The academic background and project-based learning approach suggest a proactive and self-motivated individual. However, without more information on team dynamics or collaborative projects, a full cultural fit assessment is limited.

Soft Skills & Operational Fit

The candidate's resume indicates a strong drive for practical application of AI technologies and a focus on building end-to-end systems. The academic projects suggest an ability to work independently and apply theoretical knowledge to solve real-world problems. However, without specific work experience or psychometric test results, it is difficult to assess collaboration, stress handling, or other operational soft skills.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

CSE Investment Assistant (In Progress)

January 1, 2026 – Present

Built an ML pipeline for Colombo Stock Exchange data processing and prediction. Trained Random Forest and XGBoost models for identifying profitable stock trends.

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BankIntel AI Chatbot (Banking Intelligent Assistant)

January 1, 2024 – June 1, 2026

Built a hybrid AI chatbot combining a fine-tuned BERT model for intent classification with a RAG pipeline using a locally hosted LLM (Ollama). Enabled document-based Q&A using ChromaDB for semantic search. Implemented an end-to-end pipeline with embeddings, retrieval, and LLM response generation, integrated with a FastAPI backend and Flutter mobile app.

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AgroVision - Potato Disease Detection

January 1, 2024 – June 1, 2026

Developed a CNN-based potato disease classifier for Early Blight and Late Blight using TensorFlow/Keras, achieving 96.75% test accuracy on the evaluation dataset.

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Book Recommendation System

January 1, 2024 – June 1, 2026

Developed a content-based recommender using SentenceTransformers and a collaborative filtering system using KNN and SVD to improve recommendation quality.

View Project

Key Strengths

Strong foundational knowledge in Machine Learning and Deep Learning, evidenced by academic projects.
Practical experience with various AI models including BERT, CNNs, Random Forest, and XGBoost.
Proficiency in building end-to-end AI applications, including backend (FastAPI) and mobile integration (Flutter).
Experience with LLM-based RAG pipelines and semantic search using ChromaDB and SentenceTransformers.
Demonstrated ability to work with diverse data tools like Pandas, NumPy, and DuckDB.
Clear interest in production-ready AI systems and scalable intelligent applications, aligning with an AI Engineer role.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Pathum Dilhara

Key Strengths

Cultural & Operational Fit

About

Top Skills

Skills

Education

Projects

Key Strengths

Cultural & Operational Fit