# Patrick Phelan

> Software Engineer @ Crusoe | AI Infra, HPC

Location: San Francisco, California, United States
Profile: https://flows.cv/patrickphelan

With a Bachelor's in Artificial Intelligence and a minor in Statistics from Carnegie Mellon, my journey has led me to Crusoe, where I am actively building cutting-edge AI/ML infrastructure. Our team is at the forefront of integrating advanced AI techniques to drive innovation and efficiency.

Parallel to my role at Crusoe, I contribute as a Teaching Assistant at CMU’s School of Computer Science, where we empower students with knowledge in Deep Reinforcement Learning and Control. This dual engagement with both industry and academia shapes a unique perspective, enabling me to deliver exceptional value through a blend of theoretical knowledge and practical application.

## Work Experience
### Software Engineer @ Crusoe
Jan 2024 – Present | San Francisco Bay Area
Building Stargate, Mr. Kubernetes

### Teaching Assistant - Deep Reinforcement Learning and Control (PhD) @ Carnegie Mellon University School of Computer Science
Jan 2024 – Jan 2024
▪ Hold office hours and guide students through topics such as Policy Gradient Methods (PPO, TRPO, NPG), Deterministic Policy Gradients (DDPG), Evolutionary Methods for Policy Search, and Model-Based RL. I also cover more foundational topics like Multi-Armed Bandits, Monte Carlo methods, Temporal Difference Learning, and exploration techniques such as Thompson Sampling and UCB

### Software Engineer @ Amazon Web Services (AWS)
Jan 2023 – Jan 2023 | Seattle, Washington, United States
▪ Developed EC2 console widget, leveraging AWS services and CDK to architect a scalable backend infrastructure consisting of Lambda, DynamoDB, and API Gateway.
▪ Applied two newly inherited frameworks, the widget framework and EC2 test console framework; and implemented tool to alert users of the statuses of their EC2 requests in real time; previously no support for notifying user of failed launches.
▪ Assisted senior engineers by guiding the setup of new widget development environments; created documentation on communication protocols between the two systems to simplify future development processes.

### Residential Assistant @ Carnegie Mellon University
Jan 2021 – Jan 2023
▪ Mentored a community of 200+ residents over 2 years; hosted events w/50+ residents in attendance

### Research Assistant - Center for Atmospheric Particles @ Carnegie Mellon University
Jan 2021 – Jan 2021 | Pittsburgh, Pennsylvania, United States
▪ Developed automation tool to seamlessly merge and synchronize sensor data across the lab’s measurement devices: gas chromatograph, PTR-MS, gas concentration analyzer, and lab jack
▪ Implemented a low-cost regression model (~$150) utilizing statistical software such as R, pandas, and Excel; achieved comparable performance to a high-end methane sensor worth $20,000.

### 15-210 Sequential & Parallel Algorithms and Data Structures Teaching Assistant @ Carnegie Mellon University School of Computer Science
Jan 2022 – Jan 2023
▪ Co-instructed a group of 30 students for CMU’s 15210 Sequential & Parallel Algorithms and Data Structures class through engaging weekly recitation sessions; conducted code reviews; provided personalized guidance to struggling students
▪ Collaborated with course instructor and fellow TAs to ensure consistency in course delivery, align grading standards, and contribute to the overall enhancement of the learning experience
▪Topics taught range from basic DP to graph contraction, MSTs, and randomized algorithms   
▪Class taught entirely in SML

### Software Engineering Intern @ RedZone Robotics, Inc.
Jan 2022 – Jan 2022 | Warrendale, Pennsylvania, United States
▪	Evaluated 3D reconstruction software, Meshroom, for sewer system inspections, determining its ability to handle terabytes of data and generate panoramic images.
▪	Replaced the need for inspections using thousands of 2D images with an interface akin to Google Maps' Street View by implementing Meshroom pipeline to assemble individual panoramic images into seamless 360-degree videos.
▪	Suggested hardware updates to improve renders such as camera selection, rig calibration, field of view, camera position, camera-synchronization, and sensor size; provided pros and cons alongside each proposed update.

### Data Science Intern @ Eargo
Jan 2020 – Jan 2020 | San Jose, California, United States
▪ Conducted analyses on direct-mail, tv, and email campaigns
▪ Built SQL queries and integrated salesforce, postie, and dial800 data to create automated self-updating reports to track KPIs for CMO and VP of marketing
▪ Developed new data-ecosystem and reporting tools in Google Data Studio to organize multiple data sources and facilitate weekly reporting
▪ Conducted market research to evaluate upcoming tv-creatives; analyses aided in determining tv-creative direction

### Intern @ One Hundred Feet
Jan 2019 – Jan 2019 | Palo Alto
▪ Developed data-analytics program to manage and track driver performance
▪ Streamlined data-processing system for billings department by automating weekly driver payment reports; reduced driver payment processing times from 2-3 hours to under 15 seconds


## Education
### B.S. Artificial Intelligence in Minor in Statistics
Carnegie Mellon University

### Bachelor of Science - BS in Artificial Intelligence
Carnegie Mellon University School of Computer Science

### Lynbrook High School


## Contact & Social
- LinkedIn: https://linkedin.com/in/patrick-phelan007

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Source: https://flows.cv/patrickphelan
JSON Resume: https://flows.cv/patrickphelan/resume.json
Last updated: 2026-04-11