Afreen Fatima
@afreenf193
ML Ops Engineer at Micron Technology
Hyderabad, Telangana, India
Afreen Fatima is an ML Ops Engineer with 4+ years of experience building end-to-end machine learning pipelines. She specializes in automating model training, deployment, and monitoring using Python, CI/CD tools, and containerization. Experienced in ML platforms like MLflow and SageMaker, she has a strong background in cloud infrastructure and distributed data processing. Afreen has a proven track record of productionizing models with robust governance, automated retraining, and drift monitoring across AI and semiconductor domains.
Experience
Product Development Engineer
Micron Technology
Built and maintained end-to-end ML pipelines for chipset readiness prediction and firmware validation. Automated model deployment using CI/CD pipelines with Jenkins and GitHub Actions, reducing deployment cycles by 40%. Managed model versioning and experiment tracking using MLflow for 50+ experiments. Monitored model performance and data drift for 2,000+ chipset records. Deployed containerized ML microservices using Docker and Kubernetes. Implemented governance, security, and access controls for ML workflows. Optimized MySQL database schemas, improving dashboard response times by 35%.
Prompt Engineer
Micro1
Designed and automated end-to-end ML pipelines, achieving a 47% reduction in execution time. Built YAML-driven pipeline configurations for hyperparameter tuning and experiment orchestration. Developed automated retraining workflows triggered by performance thresholds and data drift. Deployed containerized ML solutions using Docker and integrated inference endpoints into CI/CD pipelines. Tracked model experiments using MLflow. Leveraged GPU acceleration (CUDA) with TensorFlow and PyTorch. Integrated computer vision pipelines (OpenCV) into production workflows.
Business and Marketing Analyst
Softsensor AI
Built and maintained automated ML pipelines for marketing analytics using Python and Shell scripting. Implemented model monitoring and performance tracking, achieving a 20% improvement in forecast accuracy. Managed model lifecycle using GitHub workflows and YAML-based CI configurations. Optimized computer vision models for image recognition, enhancing automation throughput by 25%. Developed data preprocessing pipelines using OpenCV and Spark for large-scale image and structured data processing.
Data Science Intern – ML Pipeline Development
AI Variant
Developed end-to-end ML pipelines for time series anomaly detection on 3TB+ of unstructured data. Built and maintained CI/CD pipelines using Jenkins for automated model testing and validation. Implemented multi-threaded data processing pipelines, reducing processing time by 20%. Managed model versioning and reproducibility through structured Git workflows. Developed and deployed predictive models (decision trees, regression, SVM) with automated performance monitoring.
Education
Osmania University
Master’s
Computer Science
Machine Learning, LLM, Statistics, Probability, Discrete Mathematics
Steinbeis University
Diploma
Data Science
Python, MySQL, Machine Learning, Big Data Analytics, R