Open to opportunities

Jonathon Gibbs

@jonathongibbs

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ML Engineer & Research Associate building production deep learning and LLM systems.

Zimbabwe

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What I'm looking for

I’m looking for a role where I can own the full ML lifecycle—building reliable ETL, deploying low-latency APIs, and integrating GenAI/LLM workflows into real workflows with strong engineering standards and real cross-functional impact.

I’m an ML Engineer and Research Associate with a PhD in Computer Science and a decade of experience developing production ML systems. I design, build, and deploy machine learning models from initial concept and experimentation through to live, production-grade tools used daily by domain experts.

I work across the full model lifecycle—training custom deep learning architectures, orchestrating multi-agent LLM workflows, and deploying scalable full-stack applications. My generative AI experience includes developing custom DCNNs and deploying DCGANs for synthetic training data, along with evaluation frameworks to measure performance and mitigate bias. I also develop reinforcement learning and metaheuristic approaches (including QV-learning) to solve large-scale scheduling problems.

I deliver robust MLOps and backend services by packaging trained models into low-latency APIs with FastAPI and Docker, supported by ETL pipelines and ML infrastructure built for reliability and continuous data flow. Earlier in my career, I built high-volume ETL and predictive analytics at the NHS and Lockwood Publishing, including automated analytics, A/B testing frameworks, and internal tooling—then supported teams through technical mentorship, testing protocols, and cross-functional delivery.

Experience

Work history, roles, and key accomplishments

Current

Research Associate (ML)

Current

The University of Nottingham

Oct 2017 - Present (8 years 8 months)

Designed, built, and deployed machine learning models from initial concepts to production-grade tools used by domain experts. Engineered scalable ETL/ML infrastructure and packaged low-latency model APIs with FastAPI and Docker, while developing deep learning and reinforcement learning solutions.

Python PyTorch ETL fastAPI Docker DCGANs Reinforcement Learning Prompt Engineering DCGAN

Prescribing Analyst

NHS

Feb 2014 - Sep 2014 (7 months)

Built scalable data extraction and transformation workflows for NHS prescribing datasets using T-SQL and SSIS. Applied statistical and predictive modelling to forecast prescribing trends and automate reporting to reduce stakeholder delivery latency.

T SQL SSIS Statistical Modelling Forecasting

Senior Analyst

Lockwood Publishing Limited

Feb 2011 - Jan 2014 (2 years 11 months)

Architected and maintained high-volume ETL pipelines to extract, clean, and process millions of telemetry records for near real-time analysis. Developed predictive models and A/B testing frameworks, built internal full-stack analytics tools, and led a four-person development team to deliver software aligned to business requirements.