As a Machine Learning Engineer, I’m driven by the challenge of developing and implementing efficient and effective machine learning models that drive significant value for businesses. With 5+ years of experience and a strong background in machine learning algorithms and various technologies, I specialize in building, testing, and deploying models that meet the needs of the business. I have deployed ML solutions in the Tech and Pharma industries, where I have developed a different types of ML models such as deep learning and regression models and worked with diverse data types like images and text. My educational background (BS & PhD) is in Biomedical Engineering, which afforded me an expertise in scientific computing. I love all things data, Machine Learning and Python and aim to stay abreast of new developments in this space.

Collaboration is another aspect of my work that I enjoy, and I work seamlessly with cross-functional teams and stakeholders to ensure that the machine learning solutions I develop meet their needs and address their challenges. My strong track record of managing projects across multiple teams and delivering on time has led to mentoring more junior team members.

Please reach out if you are interested in connecting!

My Interests

I’m passionate about leveraging the latest developments in:

• ML Model Deployment/MLOps
• Generative AI - code, images and text
• Graph Data Science
• Computer Vision
• Probabilistic Programming
• Natural Language Processing & Generation
• web3 (NFTs, DeFi, DAOs & crypto)
• Camogie

Tools

• Python
• TensorFlow/ PyTorch
• Azure/AWS Cloud Services
• Azure DevOps/ Databricks
• HTML/CSS
• Javascript
• Bash/Shell Scripting
• SQL/HiveQL
• Sqlite/Snowflake/Postgres/Oracle
• Git/GitHub/GitLab
• Spotfire/Power BI/Tableau
• Neo4j
• Docker
• Confluence & Jira

Background

• BS in Biomedical Engineering, Johns Hopkins University
• PhD in Bioengineering, Pediatric Brain Injury Biomechanics Lab, University of Pennsylvania