Profile of Liam Abrams

Liam Abrams

Aspiring Machine Learning Engineer & Data Scientist

Transforming complex data into intelligent solutions. Currently seeking challenging opportunities where mathematical precision meets innovative technology.

What I Bring

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Machine Learning Engineering

Building and deploying ML models with expertise in feature engineering, model tuning, and production deployment. Passionate about creating intelligent systems that solve real-world problems.

Software Engineering

Strong foundation in Python, C/C++, and software architecture. Experience with test automation, package development, and debugging complex systems from UI to embedded software.

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Data Science & Analysis

Transforming raw data into actionable insights through NLP, statistical analysis, and exploratory data analysis. Experienced with modern ML libraries and tools.

My Journey

2023 - 2024

ML Engineering Bootcamp

Deep dive into machine learning engineering at UC San Diego. Built LIRecommend, a personalized job recommendation system, showcasing end-to-end ML development.

2019 - 2023

Software Engineer @ FLIR

Developed test automation frameworks, built Python packages, and debugged embedded software. Gained exposure to embedded C programming and thermal camera signal processing.

2018

Engineering Intern @ FreeWire

First engineering role developing touch screen interfaces for EV charging stations. Learned the fundamentals of robust, maintainable code in a startup environment.

2014 - 2019

UC Santa Barbara

Dual degrees in Mathematics and Physics. Found passion for data science through participating in a team project using NLP to analyze TV show transcripts.

Featured Project

LIRecommend

Python Machine Learning NLP Recommendation Systems

A personalized job recommendation system that learns from user preferences and job posting interactions. Built as my capstone project, it demonstrates end-to-end ML engineering from data preprocessing to model deployment.

View on GitHub

Let's Build Something Amazing

Ready to tackle challenging problems with data-driven solutions. Let's connect and explore opportunities together.