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elahe
Large Language Models Engineer
Contacto
Competencias
Demonstrated experience with Python.
Demonstrated experience with Java.
Demonstrated experience with R.
Demonstrated experience with SQL.
Demonstrated experience with C/C++.
Educación
Resumen
Professional profile
Experiencia
Large Language Models Engineer
Developed LLM-powered agents tailored to reason, plan, and use tools to automate knowledge retrieval and decision support, and built LLM-as-a-judge evaluation workflows to assess agent performance in the absence of ground truth.. Developed an end-to-end raw material price forecasting system using univariate and multivariate time-series models using frameworks such as skforecast, and built an OCR + LLM pipeline to extract sentiment signals from industry reports and incorporated them as exogenous variables in forecasting models.
Graduate Research Assistant
Developed a time-series-based malware detection and anomaly-detection system for cybersecurity applications, using PyTorch, sktime, and tsai to analyze hardware performance counter (HPC) data.. Built a sandboxed Linux container for malware monitoring and ETL pipeline to preprocess and transform HPC data for real-time machine learning analysis.. Applied Stackelberg Security Games, enabling optimized decision-making for malware detection and response.
Undergraduate Research Assistant
Developed a detection system using time-series based ML algorithms to classify network traffic and identify DDoS attacks.. Implemented models such as ARIMA and LSTM for accurate, real-time anomaly detection and validated system performance with real-world network traffic data and improved the training efficiency by 10%.
Data Science Intern
Analyzed and visualized the 2020 university entrance exam data for pattern recognition and clustering.. Used unsupervised learning approaches to identify trends in student performance and achieved close to 90% accuracy in predicting national exam scores using TensorFlow and Keras for model training.