Lead AI / ML Researcher – July 2022 – May 2025 

• Led a team to deliver a comprehensive AI/ML initiative, resulting in operational efficiency and revenue increase.
• Spearheaded the design and deployment of transformer-based vehicle detection models, improving ANPR accuracy by 32% and reducing false positives by 25%, directly increasing citation revenue by over £500k annually across council partners.
• Led the integration of vector search (FAISS) and ONNX-optimized LLMs to enable retrieval-augmented generation in regulatory document chatbots, reducing compliance query resolution time by 60%.
• Architected cloud-agnostic training pipelines (Docker, Airflow, Kubernetes) across AWS; accelerated model retraining cycles by 3x while lowering cloud compute costs by 28%.
• Implemented MLOps best practices (CI/CD, GitHub Actions, MLflow), increasing model deployment velocity by 40% and improving traceability and rollback safety for critical model releases.
• Collaborated with cross-functional stakeholders, enabling the launch of real-time predictive pricing tools that led to a 15% increase in parking bay utilisation across trial locations.

Research Assistant – Jan 2022 – July 2022

• Contributed to cutting-edge AI research, enhancing model accuracy and efficiency.
• Developed a scientific text classification framework using HuggingFace and GAN-based data augmentation, boosting F1 score by 19% on imbalanced biomedical corpora.
• Deployed models on GPU-enabled AWS EC2 instances with SageMaker endpoints, enabling sub-500ms inference speeds for live query applications in pharma RD.

ML Engineer – Sept 2019 – Aug 2020

• Developed predictive models and contributed to data science projects, enhancing business insights. 09/2019 – 08/2020
• Built scalable OCR + NLP pipelines for 100k+ document processing per month, reducing manual review time by 70% and saving
  £120k/year in labour costs.
• Created modular Python REST APIs serving model predictions to B2B clients, increasing API adoption by 45% in 3 months post-
  launch.

Consultant – April 2019 – Sept 2019

• Provided technical support and solutions for CRM’s, achieving high customer satisfaction. 04/2019 – 09/2019
• Developed document conversion algorithms leveraging NLP, OCR, and SQL, improving legacy data usability by 20%.
• Supported data visualisation pipelines for strategic reporting and customer acquisition.

ML Intern – April 2019 – Sept 2019

• Created predictive models, improving decision-making accuracy and client returns by 20% 04/2019 – 09/2019
• Delivered NLP modules for clause classification and contract segmentation; improved clause tagging accuracy by 22%, leading to faster contract review turnaround times for enterprise clients.

EDUCATION 

Sept 2020 – Oct 2021 MSc Computer Science Artificial Intelligence

Relevant Coursework: Machine Learning, Natural Language Processing, Deep Learning, Agents Multi-Agents and Reinforcement
Learning, Data Visualization, Web and Network Science, Optimization.
Thesis: Reproducing Irish Traditional Music with the help of the GAN algorithm using ABC files as input. Developing an algorithm
for GAN comprising of LSTM for generation and discrimination.

April 2016 – April 2020 BSc Computer Engineering

Relevant Coursework: Artificial Intelligence and Robotics, Machine Learning, Data Analytics, Data Mining and Warehousing.

For further information on this candidate please use reference number:  066