I'm Oliver, a Machine Learning Engineer & Researcher based in Charlotte, NC, with a dual focus on empirical research in MTL and production deployment within MTL as well as RL and post-training. I graduated with a B.S. in Computer Science from Appalachian State with a minor in Mathematics and a Data Science certificate. I'm now full-time as the sole ML Engineer at a stealth, pre-launch startup I joined after graduating. My research interests sit are in multi-task learning, reinforcement learning, and NLP.

I joined the startup orginally as an intern after my capstone project which was an ML harmonization system and real-time inference dashboard which became the initial production system for the startup and what I've been building onwards from, it's now much more comple than that. Today, I'm the sole MLE on our 4-person team, owning all ML architecture, DB, api, research, and production decisions regarding AI whithin our app and business

Coursework & self-study

A lot of my depth in ML, DL, and RL comes from deliberate self-study on top of my curriculum from university. I've worked through Stanford courses completely, watching full lectures, writing notes, doing problem sets, and exams.

Stanford (self-directed, lectures + exams + notes): CS229 Machine Learning · CS230 Deep Learning · CS336 Language Modeling from Scratch · CS224R Deep Reinforcement Learning · CME295/296 Transformers & LLMs.

Appalachian State: Applied Machine Learning · Advanced Reinforcement Learning · Artificial Intelligence · Computer Systems Numerical Methods · Computational Mathematics · Statistical Data Analysis · Linear Algebra · Theoretical Computer Science · Programming Langauges (Functional Programming w/ Haskell) · Data Structures & Algorithms.

Other: DeepLearning.AI Machine Learning Specialization (Andrew Ng) — see certifications below.

Notable academic projects from university

Formal language interpreter with lambda calculus and type inference (Haskell) · pipelined CPU simulator (C/C++) · 2D game engine (Java). My senior capstone was an ML harmonization system and inference dashboard that led to what I've expanded on at the startup, it formed the foundation of my full-time role.

Reach out

I'm heads-down at the startup, but I always like talking to people working on hard ML problems, especially those with interests in post-training, RL, NLP, MTL, the works. If that's you, get in touch.