About
Highly motivated Software Engineer Intern with a strong foundation in Machine Learning, IoT, and DevOps, currently driving real-time inference solutions and reducing system downtime by 25%. Possessing a proven ability to design and implement robust ML pipelines, automate CI/CD processes, and develop impactful, data-driven applications, I am seeking to leverage my expertise in a challenging Software Engineer or ML Engineer role.
Work
Not Specified, Not Specified, India
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Summary
Currently contributing as a Software Engineer Intern, focusing on ML pipeline development, system optimization, and CI/CD automation for IoT solutions.
Highlights
Engineered ML pipelines for predictive maintenance on IoT streams, processing over 20,000 events daily for real-time inference via FastAPI and reducing system downtime by 25%.
Trained and evaluated machine learning models using TensorFlow and scikit-learn, achieving a 12% increase in F1 score and an 18% reduction in false alarms.
Implemented robust drift monitoring and feature validation strategies, stabilizing weekly model performance and reducing retraining cycles by 30%.
Automated CI/CD pipelines for ML deployments leveraging GitHub Actions and Docker, significantly shrinking release times by 40%.
Skills
Programming Languages
Python, SQL, JavaScript.
Backend & APIs
FastAPI, Flask, REST APIs, Docker, GitHub Actions, OOP.
Data Engineering
pandas, NumPy, PySpark, Databricks, ETL Pipelines, Data Lakehouse, Power BI.
Cloud & DevOps
AWS (EC2, S3, Lambda, Redshift, SageMaker, IoT Core), Kafka, CI/CD.
Machine Learning & AI
scikit-learn, TensorFlow, Hugging Face, LangChain, RAG, MLflow.
Databases
PostgreSQL, MySQL.