Technical Skills
AWS
Spark
Kafka
Airflow
PostgreSQL
Docker
TerraformAWSSparkKafkaAirflowPostgreSQLDockerTerraformBuilding the data infrastructure that ML systems run on. S3, SageMaker, Lambda, Airflow, Spark, the AWS stack that moves data from source to model to insight.
My cloud and data work is directly tied to production ML systems. At DentalScan I built AWS SageMaker retraining pipelines with S3 data versioning and automated model promotion. At Qure.ai I maintained AWS-hosted inference endpoints serving live clinical systems. My academic work uses AWS for distributed LLM training storage and result logging. I hold both AWS Data Engineer Associate and Microsoft Fabric Data Engineer certifications.
AWSSparkKafkaAirflowPostgreSQLDockerTerraformAWSSparkKafkaAirflowPostgreSQLDockerTerraformSorted by most recently updated on GitHub
Loading...
Machine Learning Engineer Intern
Dec 2025 - Feb 2026
Architected AWS SageMaker retraining pipeline with S3 data versioning, automated model evaluation, and staged deployment. Managed data ingestion from clinical annotation tools into training-ready formats across 50K+ labeled dental images.
AI Solutions Engineer Intern
Mar 2026 - May 2026
Operated AWS-hosted AI inference infrastructure supporting 6+ live hospital systems. Managed endpoint monitoring, scaling policies, and incident response under real-time US time zone SLAs for radiology and EMR AI systems.
Senior Software Engineer
Jun 2019 - May 2023
Designed and maintained distributed data processing services handling millions of records daily for 10+ enterprise clients. Built fault-tolerant ETL pipelines and reduced data processing latency by 40% through service refactoring and caching optimization.
Amazon Web Services • Dec 2024 - Dec 2027
Microsoft • Aug 2025
AWS pipelines, data infrastructure, or cloud-native ML deployment. Let's discuss.