Caleb Bettcher

Education
Cornell University
Aug 2026 – May 2027
Master of Computer Science
New York, NY
  • Recipient of a Cornell Tech merit scholarship
University of Colorado Boulder
Aug 2023 – May 2026
Bachelor of Science in Computer Science, Minor in Business
Boulder, CO
  • 3.92 Cumulative GPA, Dean's List, Summa Cum Laude, Accelerated 3-year track
  • CU Quants – Trading Team  ·  CU Triathlon Team  ·  CU Freeride
Work Experience
Belvedere Trading
Summer 2026
Quantitative Software Engineering Intern
Boulder, CO
  • Develop low-latency algorithms for making real time decisions in electronic trading systems
  • Apply quantitative and statistical methods to identify market inefficiencies
  • Interface with market data pipelines and APIs in performance-critical environments
Handshake AI Solutions
Aug 2025 – June 2026
Prompt Engineer / AI Research Fellow
  • Design and implement structured, complex prompts in niche academic fields such as SAT/SMT solvers and advanced algorithmic reasoning to evaluate and fine-tune Large Language Models
  • Analyze and resolve internal model reasoning failures to improve reliability and interpretability of AI systems
YouTube
Apr 2020 – Present
Content Creator
  • Built a YouTube channel with over 80,000 subscribers and 10 Million views across 150 videos
  • Hired an editor to streamline video production, and help generate revenue through sponsorships with companies such as Supercell
Net-Results Marketing Automation
Summer 2022 & 2023
Full Stack Web Development Intern
Denver, CO
  • Built React frontend and GraphQL backend features enabling customizable automated marketing for 20,000+ active users
Research & Projects
Quantitative Trader – CU Quants, University of Colorado Boulder
January 2026 – May 2026
  • Monitored live market-making systems across 12 stablecoin instruments on Kraken US and OKX US, helping achieve a 98.44% uptime across a 1–178 bps spread capture range
  • Made real-time decisions during periods of unexpected market movement, contributing to 137.63% annualized returns
  • Contributed to proprietary trading dashboard and custom asset allocation engine, preparing systems for expansion to Gemini US
SurfaceEdge – Novel CNN Options Pricing Model from Surface Images
January 2026 – May 2026
  • Engineered a novel multimodal deep learning pipeline combining CNN-encoded options surface images with contract-level scalars across 200M+ labeled contracts from 17 years of historical data, extending prior computer vision research from CU ML lab work
  • Adapted a causal self-attention transformer to model price history as a sequence prediction problem — analogous to next-token prediction in LLMs — achieving best performance across all architectures
  • Designed and compared three model architectures achieving 7.9% improvement in MAE over the naive baseline
Machine Learning Research – University of Colorado Boulder
Aug 2024 – May 2025
  • Developed custom methodology software to generate datasets from multi-dimensional satellite data spanning over 6 years
  • Trained and evaluated custom YOLO models in PyTorch to identify particle-precipitation signatures in optimized plots of satellite data
  • Presented on the application and optimization of ML/AI to astrophysics at a national research conference
Skills & Expertise
  • Languages - Python, JavaScript, Julia, C++, Java, SQL
  • Frameworks/Libraries - PyTorch, YOLO, React, Laravel, GraphQL
  • Technical Skills - Git, HPC Clusters, Machine Learning, Computer Vision, Data Analysis, Financial Analysis
  • Professional Skills - Critical Thinking, Project Management, Leadership, Communication, Technical Writing
  • Certifications - TestOut - Network Pro, TestOut - Linux Pro, Handshake - Model Validation 2 (Expert)
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