"Working at Driveline was an incredible opportunity and period of self development for me. Every day consisted of thought provoking, detailed, and collaborative work with people who had a passion for understanding and innovating. It’s an environment where intelligently applied hard work leads to huge results." -Jesse Clingman, former Sport Science Intern.
Job Questions:
Why do you want to work at Driveline Baseball as your first choice? What about this company makes you want to take the opportunity over similar ones with MLB organizations or more lucrative opportunities in industries such as finance?
What are three books you've read, deep video series you've watched, or detailed technical papers in the last 12 months that have impacted your personal or professional life, and how did they change your thinking?
What agentic coding platforms have you used and how have you used them? Are there ways you have used them or would like to use them in unconventional ways?
What is the toughest problem you've had to solve in the field of mathematics, physics, engineering, computer science, or biomechanics? Did you solve it? If so, how? If not, what was the limiting factor, and what did you learn?
What project have you worked on that you're most proud of? Attach supporting documentation in the question prompt below, if a text field is insufficient.
What is your preferred method for interacting with Large Language Models, and which ones are you interacting with on a daily basis and why? Do you use different models for different tasks? What is your favorite LLM and why?
If you were tasked with fine-tuning a Large Language Model on a corpus of Driveline's data, how would you start analyzing the project? What methods would you choose and why? (You can use AI research for this, but answer in your own terms and be honest about your understanding of the technology.)
If you were tasked with fine-tuning a Vision Model on a corpus of Driveline's data, how would you start analyzing the project? How would you set up an annotation platform? What methods would you choose and why? (You can use AI research for this, but answer in your own terms and be honest about your understanding of the technology.)
Did you participate in the Kernel Optimization Challenge that Anthropic released in early 2026? If so, do you have a verified submission? More importantly, did you beat our CTO? (1329 cycles) If you participated, give details on your approach to the optimization problem.
Driveline Baseball supports three corporate locations, two partnership locations, and an undisclosed number (less than 20) of external Launchpad partners with mostly similar infrastructure needs. Assume you find a bug in the backend code that operates a Launchpad at one of our college partners that likely is a dormant bug that impacts all installations, but hasn't yet. The bug is deep in complicated Python code running on Linux machines - no data is lost, but it is both high in priority and severity. What are the first steps you take to diagnose and document the problem? Assume that Kyle does not get back to you for 45 minutes. What will you endeavor to send him in that time period? Give a timeline on when you notify the CTO (Kyle Boddy) of the issue, what the first message would be, and what you anticipate your follow up will be based on your analysis.
What is your level of proficiency in conversational Japanese? (1 = Not Proficient at All, 5 = Native or Near-Native Speaker)
