Multidisciplinary Software Engineer in Semiconductors

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Ahmed ElHoffy

USA Permanent Resident

Master of Science in Computer Science Georgia Institute of Technology Master of Science in Electrical & Computer Engineering California State University – Long Beach SUMMARY

• Software Engineer with 3+ years of experience in the semiconductor industry, specializing in machine learning, predictive maintenance, and real-time control software.

• Proficient in C++ and Delphi (Object Pascal) for developing and debugging equipment control systems; skilled with GitLab and JIRA for version control and issue triage.

• Applied machine learning for log and timestamp analysis, enabling faster fault detection and improving system reliability and recovery.

• Built Python/SQL data pipelines and deployed ML workflows using TensorFlow, Scikit-learn, and PyTorch for anomaly detection and process optimization.

• Experienced in electrical interconnect and PCB design, ensuring hardware–software integration; also teach data analytics and programming at Portland Community College with a hands-on approach. EDUCATION

Georgia Institute of Technology College of Computing

● M.S. Computer Science (Part-Time) Aug 2025 –June 2027 California State University – Long Beach College of Engineering

● M.S. Electrical and Computer Engineering CGPA: 3.88 / 4.00 Aug 2020 – May 2023

● B.S. Electrical and Computer Engineering CGPA: 3.85 / 4.00 Aug 2017 – Jan 2020 PROFESSIONAL EXPERIENCE

Software Engineer – Epitaxy Control Systems

ASM America, Inc. - Hillsboro, OR April 2025 – Present

• Supported and enhanced Epitaxy tool control software for semiconductor manufacturing, ensuring reliable operation of real-time process control modules.

• Developed, debugged, and maintained C++ backend and Delphi (Object Pascal) front-end code; reproduced and resolved complex software/hardware issues using JIRA for triage and GitLab for version control.

• Performed root-cause analysis through code tracing and step-through debugging in Visual Studio, identifying timing, synchronization, and signal-handling faults.

• Applied machine learning techniques to analyze error logs and timestamps for pattern recognition and predictive diagnostics, improving issue triage speed and recovery accuracy.

• Collaborated with cross-functional teams (software, QA, and hardware) to validate fixes, conduct regression testing, and optimize subsystem communication (gas flow, temperature, safety interlocks).

• Authored detailed debug and change reports, summarizing analysis results and proposed improvements for internal design reviews.

CS Faculty Instructor

Portland Community College - Portland, OR (Remote Part-Time) Aug 2023 – Present

• Designed and taught data analytics, programming, and web development courses with real-world applications. courses, emphasizing hands-on applications in C++, Python, SQL, and Tableau.

• Developed course materials, including curriculum, quizzes, labs, and exams, and designed a Machine Learning curriculum integrating industry-relevant techniques and projects. Systems Software Engineer

LAM Research - Tualatin, OR Nov 2022 – Nov 2024

• Designed and deployed machine learning solutions for predictive maintenance, anomaly detection, and process optimization, improving wafer yield and chamber uptime.

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• Built Python/SQL automation pipelines and Tableau dashboards for real-time equipment analytics, cutting analysis time by 90% and improving accuracy from seconds to milliseconds.

• Developed deep learning models (CNNs, XGBoost, regression) using TensorFlow, Scikit-learn, and PyTorch to predict and classify defective wafers, boosting yield by 35%

• Engineered AI-driven automation for wafer recombination using synthetic data, achieving 90% accuracy and saving 1,000+ engineering hours annually.

• Partnered with process and hardware engineers to deploy models in production, enabling 85% accurate early failure detection and enhancing chamber reliability.

• Verified electrical and mechanical assemblies in Siemens NX /Creo by validating part numbers, kit contents, routing paths, and layout; reviewed schematics, harnesses, and PCB layouts for compliance and integration Graduate Research Assistant

CSULB-Department of Electrical Engineering - Long Beach, CA Nov. 2020 – Oct 2022

• Designed and implemented Python and C++ software solutions for large-scale data collection and image processing, transforming raw data into structured ML models.

• Developed Python-based deep learning models for image processing and UAV wildfire surveillance, achieving an 85% detection accuracy.

• Published findings in IEEE Conference proceedings, contributing to advancements in federated learning research.

• Optimized data pipelines and model training using SQL/NoSQL databases, reducing data processing time by 40%. Software Engineer

DataScience Middle East (SAS Golden Partner) - Dubai, UAE June 2019 – Nov 2020

• Developed SAS enterprise solutions, focusing on data analytics and machine learning for diverse clients.

• Streamlined backend processes with optimized SQL queries, enhancing data processing efficiency by 35%.

• Delivered actionable insights through text mining and visual analytics tools, increasing client satisfaction rates.

• Managed large data sets and conducted text mining using Oracle and SQL, delivering actionable insights and business intelligence to clients.

TECHNICAL SKILLS

• Programming Languages: Python, C++, SQL, MATLAB, HTML/CSS, Bash, Object Pascal

• Frameworks/Libraries & ML_Models: TensorFlow, PyTorch, Pandas, Scikit-learn, CNN, RNN, YOLO

• Platforms & Tools: Tableau, Anaconda, MATLAB Simulink, Zuken E3, iPLM, NX, Creo, JIRA, GitLab

• Techniques: Image Processing, NLP, Decision Trees, KNN, SVM, Random Forest, K-Means PROJECTS

• FL UAV-net Developed federated CNN/YOLO Image/Video models for UAV wildfire detection Aug 2021 – Oc. 2022

• R2R4-CTGT OFDM: Applied FFT algorithms to enhance OFDM signal processing Jan. 2019 – June 2019

• Smart ROBO: An Integrated Robotic Arm for Objects’ Routing & Monitoring Aug 2018 – Dec 2018

• Huffman Code: Applied this prefix code as an algorithm for Data Compression Oct 2018 – Dec 2018

• Tic-Tac-Toe Game: Implemented a two-player game on a 3x3 Board game. Oct 2018 – Dec 2018 AWARDS

- President's Honor List: - 2016, 2018, 2019 -Dean's Honor List 2016, 2018, 2020-2021, 2023

- 3rd Place Award for Senior Design Competition: - CSULB Electrical Engineering Department May 2019

• Judges were from Boeing, Aerospace Corporation, and Southern California Edison. CERTIFICATIONS Link

• Machine Learning Specialization

DeepLearning.AI Link

• Deep Learning Specialization

DeepLearning.AI

PUBLICATIONS

• A. I. ElHoffy, S. Kwon, and H.-G. Yeh, "Federated/Deep Learning in UAV Networks for Wildfire Surveillance," in Proceedings of the 2023 IEEE Conference, Wireless Telecommunications Symposium (WTS), Boston, MA, USA, April. 2023 IEEE Xplore References are available upon request.

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