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ML Engineer with 1+ years in AI/ML, NLP & Deep Learning
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Assessing your cultural and operational fit
I am a curious learner with a can-do attitude, confident in undertaking AI/ML projects and driving them to completion by solving both technical and non-technical challenges. I am seeking opportunities as a Machine Learning Engineer to apply my skills in building impactful AI solutions.
University of Moratuwa
B.Sc. Engineering (Hons.) · Biomedical Engineering
August 1, 2019 – June 30, 2024
Deep Data Insight
Machine Learning Engineer
June 1, 2025 – Present
India
VeroxLabs (PVT) Ltd
Trainee Research and Development Engineer
January 1, 2023 – June 1, 2023
India
MedQuery - Agentic Text-to-SQL Clinical Data Query System
June 1, 2026 – Present
• Built a ReAct-style agentic AI system that converts natural language questions into SQL queries and executes them against the MIMIC-IV clinical database using LangGraph • Implemented dynamic schema retrieval with ChromaDB and multi-turn state management with SQL injection prevention and automatic retry logic for failed queries • Evaluated with RAGAS metrics (faithfulness, context precision, answer relevancy) and deployed on AWS Lambda and API Gateway
Automated PySpark Word Count Pipeline
March 1, 2025 – Present
• Developed a PySpark application to compute word counts from a dataset and containerathe application using Docker. • Implemented CI/CD automation using GitHub Actions to package and push the Docker image to Docker Hub.
View ProjectChatbot using Retrieval Augmented Generation (RAG)
January 1, 2025 – Present
• Developed an intelligent chatbot that uses retrieval-augmented generation (RAG) to generate accurate responses tailored to a specific domain.
View ProjectfNIRS acquisition device for measuring cognitive load (Final Year Project)
April 1, 2024 – Present
• Developed an fNIRS acquisition device to observe the functionality of the brain. • Performed data collection and signal pre-processing. • Implemented SVM, k-NN, Logistic Regression, CNN, and LSTM models to classify cognitive load levels. • Evaluated and selected the best-performing model among the implemented models.
Supervised Machine Learning: Regression and Classification
DeepLearning.AI
June 1, 2026 – Present
Advanced Learning Algorithms
DeepLearning.AI
June 1, 2026 – Present
Databases and SQL for Data Science with Python
IBM
June 1, 2026 – Present
Agentic AI
DeepLearning.AI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from agentic text-to-SQL systems to fNIRS device development and PySpark pipelines, indicates a broad interest and adaptability. The academic background in Biomedical Engineering combined with practical ML experience suggests an interdisciplinary mindset. The current role as a Machine Learning Engineer at Deep Data Insight and the target role alignment are strong. The certifications from DeepLearning.AI further demonstrate a commitment to continuous learning and staying current with industry trends. The candidate's involvement in university clubs and leadership roles also points to a collaborative and engaged personality.
Soft Skills & Operational Fit
The candidate's 'About Me' section highlights a 'curious learner with a can-do attitude' and confidence in solving 'technical and non-technical challenges'. Project descriptions indicate problem-solving skills (e.g., SQL injection prevention, automatic retry logic) and a structured approach to evaluation (RAGAS metrics). The 'Positions of Responsibility' section suggests leadership and teamwork capabilities. Overall, the candidate appears to be a proactive and capable individual, suitable for a dynamic ML engineering environment.