John Evan Owen - CTO & AI Engineer Portfolio
"From distilling 70B LLMs on 24 H200 GPUs to scaling teams of 20+ engineers, I build AI systems that ship. Pending LLM patent, 4x inference throughput gains, 15+ production apps, and platforms handling 10,000+ TPS."
10+
Years Experience
20+
Engineers Led
15+
Apps Shipped
1
Pending Patent
Skills
Achievements
Blackbelt in Zen Shotokai Karate
Pending Patent
Systems and Methods for Generating an Improved Mixture of Attention Model
QWERKY AI Inc. · 2025
Novel LLM architecture with CUDA implementation
Education
Georgia Institute of Technology
MS Computer Science
Expected May 2028
University of South Carolina
BS Computer Science
Summa Cum Laude
GPA: 3.956 / 4.0
Programming Languages
Tools, Libraries, Frameworks, Etc.
Experience
QWERKY AI Inc.
Co-Founder & Chief Technology Officer
2025 - 2026
- Designed and built QDistill, an end-to-end post-training pipeline distilling 70B parameter teachers into 3B-8B hybrid Mamba-Transformer students via DeepSpeed ZeRO-3 on 24 H200 GPUs across 3 nodes, followed by SFT instruction tuning and RL alignment (GRPO, DPO), achieving 4x inference throughput and 1M token context length
- Contributed patches to Hugging Face Accelerate/Trainer enabling dual-model DeepSpeed plugins; invented selective gradient checkpointing for hybrid architectures saving 30-40% memory
- Curated 12M sample training dataset from 9 sources with MinHash LSH deduplication (15-20% dedup rate); generated synthetic data from Llama 3 405B; built Model-as-a-Judge evaluation using Claude and GPT
- Built comprehensive evaluation suite using lm-eval-harness across MMLU, HellaSwag, PIQA, ARC, Winogrande, plus custom speed/latency benchmarking (TTFT, TPOT, P99) with models served via vLLM; all experiments tracked in W&B and MLflow
- Developed key pending patents for LLMs with CUDA implementation, including Systems and Methods for Generating an Improved Mixture of Attention Model
- Primary external contributor of State Space Models and Mamba architectures to Modular's MAX inference framework in Mojo, authoring custom selective scan, causal convolution, and RMSNorm fused kernels
- Built a 6-person research team and a 2-engineer product department; established a rigorous interview process driving 100%+ increase in team effectiveness
MerkleRoot
Chief Technology Officer
2024 - 2025
- Managed a team of 20+ international developers and engineers
- Led teams through the successful development and launch of the company's flagship products
- Spearheaded the adoption of cutting-edge blockchain technologies and cryptography
- Key stakeholder in the company's strategic direction and transition away from staff augmentation
- Guided the engineering organization through a difficult market transition, retaining core engineers and sustaining client delivery
- Developed a Solidity decompiler in Go and Rust that was a key feature in the company's product Hexman
- Optimized Solidity codebases and EVM instruction sets, driving significant reductions in gas fees and bytecode size
- Performed a security audit on a client's smart contract, identifying and fixing 5 critical vulnerabilities
VP of Architecture
2022 - 2024
- Led technical strategy and architecture across all major client projects
- Increased client allocation and revenue by 300% in 1 year
- Created the process for technical screenings and mentorship within the company
- Led hiring, conducted technical interviews, code reviews, and mentored developers
- Grew team from 9 to 20+ engineers in 1 year
- Spearheaded the adoption of asdf and Nix for development and deployment, reducing environment setup time
- Developed white papers and technical design documentation and established best practices for the company
- Primary architect for the company's main client, Forte
Forte
Architect
2022 - 2024
- Led 8 teams of 5-7 engineers to deliver a new blockchain platform for the gaming industry at 1 million concurrent users
- Architected Platform X and the Forte Protocol with a focus on developer experience and scalability
- Designed byte-level metadata standard enabling the storage of 1+ million JSON NFTs on Ethereum with significant gas and storage cost reductions
- Designed a multi-tenant, multi-region, and multi-layered architecture for Platform 2.0 with core abstractions in the Blockchain Layer and Orchestration Layer
- Built Go services for Platform 2.0's core, including the Bridge, Orchestration, and API Layers, enabling gaming studios to run live in-game economies at production scale
- Built Go microservices and programming language SDKs for the platform
- Conducted interviews for senior leadership and directors of engineering
- Led initiative to significantly reduce platform technical debt, improving developer velocity and system reliability
First Foundry
Senior Software Engineer
2022
- Managed handoff of multiple ongoing applications as 52inc underwent acquisition by First Foundry
- Led a 3-member research team under the CTO; built high-throughput data bridge in Go at 1,000+ rps
- Built microservices in Elixir/Phoenix, Rust, and Python, integrating Ethereum, Zero Knowledge Proof, and Solana blockchain technologies
- Created a notification system in Elixir with Erlang/OTP, delivering 10,000+ notifications per second
52 Inc.
Senior Software Engineer
2019 - 2022
- Delivered 15+ apps and platforms to clients across healthcare, insurance, marketplace, and live streaming domains; turned around 5+ at-risk projects
- Mobile iOS app development in Swift and Objective-C
- Scaled a hospital messaging system from 100 rps to 1,000+ rps, restoring reliable real-time communication for clinical staff during peak hours
- Maintained and scaled a Kubernetes-based platform tracking 1,000+ devices in real time, enabling an emergency response company to coordinate field operations reliably
- Created document reading and searching apps for the insurance industry in Swift and Objective-C
- Built a predictive pricing model for Ventrue Resorts using LSTM and Linear Regression in TensorFlow; discovered that the inductive bias of Linear Regression outperformed the LSTM for this domain
Software Engineer
2015 - 2019
- Contributed to backend systems and APIs in Python, Java, and C++ under senior engineering guidance, supporting marketplace, healthcare, and live streaming products
- Worked with the lead engineer to design and build a redundant data pipeline for real-time device location tracking, enabling an emergency response company to monitor field assets with sub-second latency
- Implemented supervised machine learning models (kNN) for recommendation systems under mentorship, gaining early hands-on ML experience
Open Source
Projects & Contributions
Creator · 2026
Port of Andrej Karpathy's llm.c to the Mojo programming language with full GPU support; every training and inference kernel hand-written.
Primary external contributor, SSM support · 2025 - 2026
State Space Model and Mamba architecture support for the MAX inference framework, with custom selective scan, causal convolution, and RMSNorm fused kernels in Mojo.
Creator
Turns a coding CLI (Claude Code, Codex, Cursor, Gemini) into a self-directed, drainable session that lands review-shaped PRs by morning.
Creator
Syncs a local filesystem with a SQL database and vector embeddings, providing storage and serving for sovereign AI models.
Creator
Self-healing supervisor for long-running processes: watch a command, catch the failure, fix it, leave a paper trail.
Maintainer since 2018 · 2,000+ GitHub stars
Swift drawer UI library recreating the iOS 10 Maps experience, created at 52inc.
Publications
Blog Posts
February 2026
Implementing Mamba 1 architecture into Modular's MAX inference framework with custom CPU-only Selective Scan and causal convolution kernels for cross-vendor SSM support.
September 2025
A critical examination of Geoffrey Hinton's "mother AI" proposal, advocating for human-centered AI development that prioritizes sustainability and efficiency over speculative superintelligence concerns.
June 2025
Analysis of Meta's Ring Attention and DeepSeek-V3's Multi-head Latent Attention, exploring how fundamental memory and hardware constraints continue to limit LLM architectures.
May 2025
Exploring hidden sources of unpredictability in LLMs including floating-point arithmetic errors, parallel processing inconsistencies, and hardware variations affecting AI reproducibility.