🚀 AI Engineer | ML/DL Specialist | MLOps Enthusiast

🌟 A passionate Machine Learning and Deep Learning Engineer with a mission to drive positive change through technology. I specialize in building, deploying, and scaling AI-powered solutions that make an impact.

I specialize in designing, developing, and deploying AI-driven solutions with a strong emphasis on performance, scalability, and real-world impact. My technical proficiency includes:

• Machine Learning & Deep Learning: Hands-on experience with TensorFlow, PyTorch, Transformers, and Hugging Face.
• NLP & LLMs: Skilled in Retrieval-Augmented Generation (RAG), Prompt Engineering, and integrating LangChain and LLM agents for advanced automation and medical text processing.
• MLOps & Deployment: Proficient in MLflow, Docker, Kubernetes, DVC, and Airflow for scalable AI pipelines, with hands-on experience in cloud deployment on Oracle Cloud and on-premises solutions.
• Data Engineering & Visualization: Experienced in ETL processes with Talend Open Studio, Oracle database integration (cx_Oracle), and developing interactive dashboards using OBIEE and Streamlit for actionable insights.
• Programming & Tools: Python | R | SQL | PL/SQL | Git | GitHub | FastAPI | Streamlit | Jupyter Notebook | Anaconda | VS Code | OpenCV | Docker

Funding: Bill & Melinda Gates Foundation's Grand Challenges Initiative
Overview: Collaborated on a groundbreaking AI project to assess the equitable use of Large Language Models (LLMs) for clinical decision support in South Asia. Fine-tuned open-source LLMs to process electronic health records (EHRs), enabling medical concept extraction and question answering to enhance decision-making and reduce health disparities.
Tech Stack: LLMs, NLP, Python, Hugging Face.

Overview: Collaborated on an AI-driven system for generating discharge summaries, transitioning from ChatGPT API to a cost-effective, locally deployed Llama model. Optimized documentation workflows for operational efficiency.
Tech Stack: Python, Ollama, FastAPI, Oracle DB, Docker.

Overview: Built a Streamlit application for querying and analyzing radiology/nuclear medicine reports, integrating Oracle database connectivity and advanced data manipulation.
Tech Stack: Streamlit, cx_Oracle, Pandas, Polars, Docker.

Overview: Automated complex data extraction and cleansing pipelines using Python and R. Enhanced data quality and insights through advanced visualization and reporting (Tableau).
Tech Stack: Python, R, Tableau.

Check out my technical blogs on Medium:
🔗 Medium Profile

💼 LinkedIn: Sehrish Ilyas
📧 Email: sehrishilyas19@gmail.com
📂 GitHub: Sehrish Ilyas

💡 I believe technology has the power to transform lives — whether it's through AI innovation, data-driven insights, or creative tech solutions. I'm always excited to collaborate on meaningful projects. Let's build something extraordinary together!