Pradnya Gaikwad

I am a Machine Learning Engineer with two years of professional experience in AWS cloud administration, focused on bridging model development and scalable cloud deployment. I specialize in MLOps, deep learning, and predictive modeling with a strong foundation in Python and AWS SageMaker.

At Infosys, I managed high-availability cloud infrastructure using EC2, S3, RDS, Auto Scaling, and implemented automated failover strategies that improved system uptime. I automated alerting with CloudWatch and enforced IAM and CloudTrail monitoring to maintain security and compliance.

On projects, I developed a real-time fraud detection system using Scikit-learn and SageMaker for hosted inference, and built an end-to-end NLP sentiment analysis pipeline using NLTK with S3-backed data ingestion. I’ve delivered feature engineering workflows and hyperparameter tuning to improve model performance.

I bring practical experience in infrastructure-as-code and cost optimization—using automated tagging and instance right-sizing—alongside hands-on skills in NumPy, Pandas, Scikit-learn, Git, and Terraform. I am continuing professional development through a Generative AI and Machine Learning program to deepen my expertise.