I'm Jonathan Koch, an ML Engineer at Topaz Labs and Co-Founder & CTO of Hirebase. I build production ML systems spanning image/video enhancement, large-scale web ingestion, and recommendation engines. I hold a B.S. in Computer Science from the University of South Florida with a concentration in Robotics and AI, graduating Cum Laude.
My research interests center on representation learning, contrastive methods, multi-modal data processing, and GAN architectures. I've worked across the stack from model design and training to serving infrastructure and enterprise APIs.
Outside of engineering, I play acoustic guitar and piano, train Brazilian Jiu-Jitsu, and play way too much Minecraft (join my SMP: mc.jonathankoch.dev).
Timeline
Professional History
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June 2024 – Present
ML Engineer @ Topaz Labs
Designing, training, and deploying ML models for image and video enhancement used by millions. Built the flagship Autopilot feature, Portrait and Wildlife enhancement models, Auto Sharpen, Face Recovery V3, and High Fidelity V3. Led GAN architecture research producing the first whole-image conditioning model with per-tile semantics. Optimized model serving runtimes across hundreds of production models.
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November 2023 – Present
Co-Founder & CTO @ Hirebase
Built the core tech platform for an AI-powered job search engine scanning 4M+ live jobs directly from company career pages. Scaled the ingestion engine from 1M to 10M+ records per month. Now serving 150+ customers worldwide at $80K ARR. Developed token parsing models for extracting structured data from raw HTML, enterprise API features including secure resume embeddings, user recommendation systems, and prediction models on unstructured job data.
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November 2023 – May 2024
ML Engineering Co-Op @ CAE USA
Led Generative AI development on the Data Science team. Prototyped a Generative Agents architecture built on LLMs. Incorporated contrastive learning into text classification, improving accuracy from 93% to 99%. Developed pretraining pipelines for BERT models and created text augmentation libraries for structured generation.
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May 2024
Graduated from University of South Florida
B.S. in Computer Science, concentration in Robotics and AI. Cum Laude, 3.7 GPA.
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October 2021 – May 2024
Research Scientist @ RPAL (Robot Perception and Action Lab)
Developed advanced object manipulation algorithms using the Barrett Hand robot. Built multi-modal encoder architectures processing tactile, visual, torque, and joint angle data. Designed forward and inverse dynamics models for robotic manipulation tasks.
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July 2023
Founded USF IEEE AI Group
Created and led the AI special interest group within IEEE at USF. Organized workshops, led the Teach-a-Bull research project (LLM-based educational content generation), and extended collaboration to other universities via open-source software.
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May 2022 – November 2023
Junior Software Developer @ CAE USA
Began as a junior developer before being selected for the Data Science team. Worked on ML models, natural language processing, and intelligent agents for defense simulation systems.
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April 2023
VEX Worlds Competition — Dallas, TX
Represented USF at the world's largest VEXU robotics competition as part of TerriBULL Robotics. Built computer vision subsystems on NVIDIA Jetson Nano paired with the V5 Brain for autonomous robot control.
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November 2021 – Summer 2023
Programming Instructor @ theCoderSchool Tampa
Taught programming fundamentals and AI concepts to young students. Developed CoderSchoolAI, an open-source Python library for teaching reinforcement learning and agent-based AI.
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August 2021
Transferred to University of South Florida
Transferred from SUNY Albany to pursue Computer Science with a concentration in Robotics and AI. Immediately joined RPAL and USF IEEE.