Professional Summary
Ai/Ml Engineer with 5 years of experience designing scalable machine learning pipelines and deploying predictive models in cloud environments. Specialises in AWS and Azure architectures, real-time data processing, and cross-functional collaboration to drive business outcomes. Committed to building robust solutions that enhance operational efficiency and decision-making.
Skills
- AWS
- Python
- Machine Learning
- Azure
- Ci/Cd
- Kubernetes
- Flask
- ETL
- Kafka
- Tensorflow
- Pytorch
- Scikit-Learn
- Data Visualisation
- MLOps
Experience
Ai/Ml Engineer — Tata Consultancy Services
- Architected and deployed an AWS-based recommendation engine serving 2 million monthly users, increasing conversion rates by 15%.
- Optimised ETL pipelines with Apache Airflow and Glue, cutting data latency from 24 hours to 90 minutes for analytics teams.
- Led cross-functional workshops to identify ML use cases, resulting in three approved projects with measurable ROI.
- Implemented ML observability tooling that reduced model drift incidents by 40% and improved stakeholder trust.
- Mentored junior data scientists on productionisation best practices, fostering a culture of MLOps accountability.
Associate Engineer — AppleTech
- Developed and maintained machine learning models for customer churn prediction, improving retention programme adoption by 22%.
- Automated model retraining workflows using Azure ML, decreasing manual intervention time by 80%.
- Collaborated with product managers to translate business hypotheses into measurable experimentation outcomes.
- Presented findings at quarterly leadership reviews, bridging the gap between analytics outputs and strategic priorities.
- Contributed to open source data quality libraries that are now used across the engineering organisation.
Education
B.S. Electrical Engineering
Ohio State University
Certifications
- AWS Certified Machine Learning - Specialty
- Azure Data Scientist Associate
- Google Professional Machine Learning Engineer