Parking traces processed in recent generative data workflows.
AI engineer working across production ML, research, and infrastructure
Experience across production ML, research, and infrastructure.
Experience across production machine learning, research engineering, and infrastructure, with most of the recent work centered on autonomous systems and high-performance ML.
Observed MFU range on one recent generative pipeline.
Reduction in one internal height-map processing path.
Long-context target for differentiable Sinkhorn attention work.
2020—Now / Selected path
A line through research and engineering.
Move through the milestones. The line joins formal study, applied work, and the research questions that emerged between them.
01 / Foundation
2020—2024
Data science at University College Cork
Built the mathematical and computational base for later work in machine learning, while learning how technical systems meet people in a customer-facing role.
02 / Applied ML
Rotterdam · 2022
Forecasting at Agnicio
Benchmarked proprietary forecasts against LightGBM, XGBoost, and ARIMA baselines, then helped shape the work toward a more accessible SaaS product.
03 / Developer systems
Microsoft Research · 2023
Making complex systems easier to enter
Built authentication mocks and configuration tooling, evaluated Copilot output, and won internal recognition for LLM-based onboarding and education concepts.
04 / Research engineering
Microsoft Research + UCD · 2024
From tooling into medical AI
Returned to Microsoft to improve CMS preview workflows, completed the B.Sc., and began an M.Sc. focused on AI for medicine and medical research.
05 / Production ML
Valeo Vision Systems · 2025
Deep learning under real constraints
Moved into autonomous-driving workflows spanning generative data, JAX optimization, orchestration, and the infrastructure needed to make experiments dependable.
06 / Current direction
Europe · Now
Systems that make ambitious algorithms practical
Current work joins production ML with long-context attention research, including block-wise differentiable Sinkhorn attention and hardware-aware JAX kernels.
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Profile
What I bring to a team
I work best in technical environments where the work cannot be cleanly split into "research" or "engineering." I like closing the loop between those two: building the kernel, the pipeline, the orchestration, the measurement, and the test surface around it.
Most of my recent work sits at that intersection: long-context attention kernels, computer vision and generative data pipelines, scheduling and orchestration layers, large-scale processing, and systems that become easier for other engineers to trust.
Work History
Experience
Sep 2025 - Present
Deep Learning Engineer
Valeo Vision Systems • Galway, Ireland
- Built a generative AI workflow over 10,000+ parking video traces, combining segmentation, masking, and inpainting while driving utilization into the roughly 30-45% MFU range under real pipeline constraints.
- Engineered hardware-agnostic JAX optimizations that reduced one trace processing path by 89%, from 45 minutes to 5, after earlier 7x speedups in 3D point-cloud rasterization.
- Architected Airflow and Kubernetes pipelines for extraction, processing, and dynamic task routing across cloud and on-prem resources.
- Investigated agentic CI/CD workflows and documentation generation to reduce engineering friction across a complex codebase.
Jun 2024 - Sep 2024
Software Engineering Intern
Microsoft Research • Dublin, Ireland
- Developed state and API mocking systems that made previewing CMS-driven live changes faster and less operationally expensive.
- Contributed tooling that improved engineering iteration speed in both production and testing environments.
Mar 2023 - Sep 2023
Software Engineering Intern
Microsoft Research • Dublin, Ireland
- Built authentication mocking and a builder-pattern configuration framework that reduced onboarding and backend setup complexity.
- Led work evaluating Copilot output using NLP, semantic accuracy, and topic modeling techniques.
- Won internal hackathon recognition for LLM-based onboarding and M365 education concepts.
Jun 2022 - Sep 2022
Data Science & Machine Learning Intern
Agnicio • Rotterdam, Netherlands
- Benchmarked proprietary forecasting models against strong Kaggle baselines and developed LightGBM, XGBoost, and ARIMA alternatives.
- Helped transition forecasting work toward a SaaS-style offering with better accessibility and scalability.
Nov 2020 - May 2022
Showroom Sales Specialist
Dwyers Electrical • Cork, Ireland
- Worked in a team grossing roughly EUR 5M annually and introduced a chatbot to support online sales activity.
Selected Research
Projects worth highlighting
Block-wise differentiable Sinkhorn attention
Memory-efficient optimal transport attention with a custom backward pass, VMEM packing, and TPU-oriented JAX/Pallas kernels.
Research detailsDomain shift in deep RL agents
Built reactive exploration methods to quantify domain shift magnitude across OpenAI Gym environments.
Multi-omics analysis for hepatic liver cancer
Integrated genomic, transcriptomic, and proteomic signals to search for predictive biomarkers using deep learning and statistical modeling.
Education
Academic foundation
M.Sc. Artificial Intelligence for Medicine and Medical Research
University College Dublin
GPA: 3.75 / 4.00
B.Sc. Data Science and Analytics
University College Cork
GPA: 3.68 / 4.00