Software & AI Engineer with Dual Degrees

ALEXANDER BRITTAIN

Tempe, AZ

425-***-****

*******************@*****.***

Portfolio: stormpiethon.github.io

LinkedIn: https://www.linkedin.com/in/alexanderbrittain-ajb1990/ PROFESSIONAL SUMMARY

Software Engineer and Artificial Intelligence graduate with dual B.S. degrees in Computer Science and Artificial Intelligence from the University of Advancing Technology. Strong foundation in data structures, algorithms, machine learning, distributed systems, and statistical modeling. Experience building ML models, working with big data frameworks (Spark/Hadoop), implementing LLM applications, and developing full-stack software solutions. TECHNICAL SKILLS

Languages:

Python, C++, C#, Java, C (Embedded/Arduino), SQL, JavaScript, HTML, CSS Machine Learning & AI:

Scikit-learn, TensorFlow, PyTorch, NLTK, OpenAI API, Regression, Classification, KNN, K-Means, Time Series Analysis, Neural Networks, NLP, Prompt Engineering, Model Evaluation Data & Analytics:

Pandas, NumPy, SciPy, Matplotlib, Exploratory Data Analysis (EDA), Statistical Modeling, Feature Engineering

Big Data & Distributed Systems:

Apache Spark (PySpark), Spark DataFrames, Spark Streaming (Labs), Hadoop, Hive (HiveQL basics), HDFS, MapReduce (Conceptual), Scala (Foundational), Distributed File Systems Software Engineering:

Data Structures & Algorithms, OOP, REST APIs, JSON, SDLC, Agile, Git (Foundational), Bash/Linux CLI, Spring Boot, JPA, JMS, Hibernate

SELECTED PROJECT EXPERIENCE

Local LLM Application – “Quasar LLM” (Python)

• Developed localized Large Language Model interface with custom prompt engineering.

• Integrated OpenAI API and implemented tokenization and sentiment analysis using NLTK.

• Added Text-to-Speech functionality to enhance interactive response capability.

• Evaluated output consistency and refined prompts to improve contextual relevance. Machine Learning & Statistical Modeling Projects

• Built a regression model to predict housing prices using feature engineering and model evaluation techniques.

• Implemented K-Nearest Neighbors (KNN) and K-Means clustering on structured datasets.

• Conducted heart attack dataset classification analysis and evaluated model performance.

• Performed Iris dataset analysis using supervised learning methods. Time Series Forecasting – London Cycling Data

• Cleaned and preprocessed real-world dataset using Pandas and NumPy.

• Engineered time-based features to improve predictive accuracy.

• Built forecasting model and evaluated performance using statistical error metrics.

• Visualized trends and predictions using Matplotlib. Big Data Processing Labs – Spark & Hadoop

• Implemented Spark DataFrame transformations and aggregate functions using PySpark.

• Simulated streaming data processing workflows.

• Worked with Spark Sessions, partitioning strategies, and distributed computation concepts.

• Explored HiveQL queries and Hadoop ecosystem fundamentals. Algorithms & Systems Projects

• Implemented sorting algorithms and analyzed empirical runtime vs. Big-O complexity

(C++).

• Built Binary Search Tree performance analysis across varying dataset sizes.

• Developed A* Pathfinding and sorting visualizers.

• Created interactive applications in C++, C#, Java, Python, and React Native. EDUCATION

Bachelor of Science – Computer Science (2025)

Bachelor of Science – Artificial Intelligence (2025) University of Advancing Technology – Tempe, AZ

Relevant Coursework:

Machine Learning, Deep Learning, Data Structures & Algorithms, Database Systems, Distributed Systems, Linear Algebra, Statistical Modeling, Software Engineering ADDITIONAL EXPERIENCE

Operations & Team Leadership – Service Industry (10+ Years)

-Led teams in high-volume operational environments.

-Trained and mentored staff; managed scheduling and logistics.

-Demonstrated adaptability, problem-solving, and performance under pressure.

-Maintained SOPs for food and alcohol safety.

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