Machine learning Engineer with experience in ETL, NLP-based data processing, forecasting, predictive modeling, and end-to-end ML pipelines. Experienced in Python, Elasticsearch, Azure, AWS, Docker, Airflow, and machine l…
Machine learning Engineer with experience in ETL, NLP-based data processing, forecasting, predictive modeling, and end-to-end ML pipelines. Experienced in Python, Elasticsearch, Azure, AWS, Docker, Airflow, and machine learning research across biomedical and automotive data.
I am working on my thesis at Bayer where I am creating a centralized data repository for biomedical annotated data. This involves implementing named entity recognition and comparing different domain models to improve accuracy. I am also contributing to the development of a question answering system for biomedical data using GPT-J.
Implemented ETL on annotated biomedical data from different sources and parsing it to one unified format (Json).
Integrated data into Elasticsearch enabling easy utilization for machine learning research.
Developed and compared fine-tuning of domain models using Bert, with the goal of enhancing Named Entity Recognition on the integrated Elasticsearch data.
Collaborated in Research to provide solutions for Questing Answering system encompassing Data Generation, finetuning using Large Language Models and Generative AI Techniques.
Processed and transformed real-time data in different formats using Python libraries.
Handled imbalanced and missing data that yielded significant improvements in accuracy of models.
Created an NLP-based data processing preparation pipeline leading to increased accuracy, better predictions, and valuable insights, enabling faster model iteration and deployment by 20%.
Developed ML end-to end pipeline that clusters defects reported by customers in automotive components.
Co-ordinated the development and implementation of forecasting and predictive model, which helped in identifying different patterns and relations that provided impactful business processes that led to growth and innovation.
Collaborated in Agile Scrum Workflow and collaborated with Cross-functional team, gathering Business Requirements, design/execution of Python scripts to automate data triggering resulting in a 50% reduction in manual effort.
Implemented ELT process, of extracting the financial data from Relational database using (Postgres SQL) or API integration.
Evaluated data and performance metrics using data analytics tools for data Visualization and monitoring which helped provide valuable, innovative solutions to the client.
The AI-first Recruitment Operating System that unifies and automates the entire hiring lifecycle for modern enterprises worldwide.
Dr Job FZ LLC. 2026 © All Rights Reserved
