Skip to content

John Lenehan

Senior AI Developer | Data Scientist | ML Engineer

Engineering scalable AI & ML solutions. Turning complex data infrastructure into measurable business value.

Portrait of John Lenehan in the Dolomites

Tech Stack

Core languages, frameworks, and infrastructure.

Languages

PythonSQLBash

Machine Learning & GenAI

TensorFlowPyTorchScikit-learnLangChainLlamaIndex

Cloud & MLOps

GCPCloud RunVertex AIDockerAzure

Data Engineering

ChromaDBMySQLCloud SQLOracle

Expertise

Specialised domains and technical capabilities.

Generative AI & LLMs

Deploying enterprise GenAI solutions using robust RAG pipelines and custom model fine-tuning.

MLOps & Cloud Architecture

Engineering scalable, end-to-end ML pipelines and automated CI/CD deployments on cloud platforms.

ML Engineering

Building and optimising high-performance production ML models, managing the complete lifecycle and real-time serving.

Data Science & Analytics

Driving business strategy via statistical modelling, time-series forecasting, and robust A/B testing.

Experience

Professional history across Data Science and Engineering.

Senior AI Developer

Softworks|Apr 2025 – Present|Dublin, Ireland
Softworks

Leading the development of enterprise AI solutions, driving SaaS product development through secure LLM architectures and scalable MLOps infrastructure.

  • Engineered a secure hybrid LLM engine to route queries between RAG and SQL databases, while enforcing strict data isolation to minimise support ticket volume.
  • Established scalable CI/CD workflows on GCP using Docker to automate model training and deployment, designed to reduce time-to-production for new model iterations.
  • Architected multivariate time series models to forecast staff availability, identifying potential coverage dips to drive data-led staffing.

Production Data Scientist

Intel Corporation|Aug 2020 – Oct 2024|Leixlip, Ireland
Intel Corporation

Engineered and deployed production-grade machine learning and analytical systems within a high-volume manufacturing environment.

  • Reduced failure rates on critical equipment by 66%, via SQL-driven cohort analysis and A/B testing.
  • Built, optimised, and managed CNN pipelines for automated anomaly detection on high-velocity production lines, improving defect recall by 7.5%.
  • Engineered time-series forecasting for 3 major segments, handling volatile supply metrics to achieve 95%+ weekly prediction accuracy.
  • Implemented risk-scoring models for critical process junctions, reducing quality violations by 58%.
  • Led cross-functional team to drive new product certification 1 week ahead of customer commit dates.

Manufacturing Engineer

Medtronic|Jan – Aug 2018|Galway, Ireland
Medtronic

University placement designing manufacturing processes, layouts, and equipment operations for optimal efficiency.

  • Implemented modular stent assembly stations, reducing maintenance downtime from 1 week to 2 hours.
  • Designed cleanroom tools using Solidworks to prevent stent damage, reducing stent defect rate by 75%.

Qualifications

From Mechanical Engineering at NUI Galway to Applied Data Science at MIT.

Azure Data Scientist Associate

Microsoft

Microsoft
CertifiedSept 2024

Official certification for scalable machine learning and MLOps on Microsoft Azure.

  • Hands-on deployment of scalable machine learning pipelines using Azure ML Workspace.
  • Implemented automated model training, rigorous evaluation, and CI/CD deployment workflows.

Applied Data Science

Massachusetts Institute of Technology

Massachusetts Institute of Technology
DistinctionJan – May 2024

Advanced practical studies in data science and artificial intelligence.

  • Engineered production-ready deep learning models, recommendation engines, and forecasting systems.
  • Executed complete ML lifecycles, from raw data acquisition through to deployment and evaluation.

Specialist Data Analytics

University College Dublin

University College Dublin
DistinctionJan – Jun 2023

Advanced quantitative analysis, statistical modelling, and core machine learning fundamentals.

  • Applied advanced supervised and unsupervised learning, ensemble methods, and clustering techniques.
  • Conducted rigorous statistical hypothesis testing, A/B evaluation, and hyperparameter optimisation.

Master of Engineering (Mechanical)

NUI Galway

NUI Galway
1st HonoursSept 2019 – May 2020

Advanced computational modelling, numerical methods, and systems-level engineering design.

  • Engineered a programmable multi-axis test rig to conduct advanced stress failure analysis.
  • Specialised in complex numerical simulation, statistical testing, and system optimisation methods.

Bachelor of Engineering (Mechanical)

NUI Galway

NUI Galway
1st HonoursSept 2015 – May 2019

Rigorous foundation in advanced mathematics, computational modelling, and engineering design.

  • Developed computational simulations and programming frameworks for complex engineering analysis.
  • Researched and developed novel additive manufacturing processes for metal-polymer composites.

Case Studies

A curated selection of enterprise AI architectures and ML systems.

Hybrid RAG & MCP Engine

Hybrid RAG & MCP Engine

97.5%Accuracy

Agentic LLM system routing queries between RAG pipelines and MCP servers via semantic embeddings.

LangChainRAGMCPSemantic Routing
Config-Driven ML Framework

Config-Driven ML Framework

85%Time Savings

YAML-based framework for reproducible model training and artifact management, containerised in Docker.

DockerMLOpsCloud
Emergency Dispatch Routing

Emergency Dispatch Routing

91.1%Recall

Architected predictive models to classify and prioritise critical municipal dispatch operations.

Scikit-learnClassificationData Analytics
Output Time Series Forecasting

Output Time Series Forecasting

96%Accuracy

Developed and deployed Prophet time series models to forecast weekly and quarterly production output metrics.

Scikit-learnProphetTime Series
CNN-based Malaria Detection

CNN-based Malaria Detection

98.8%Recall

CNN-based classification of malaria infected cells from microscopy images (4% above WHO benchmarks).

TensorFlowCNNComputer Vision
Content Recommendation Engine

Content Recommendation Engine

81.5%Precision

Engineered a Logistic Regression classification model to prioritise high-traffic web content.

Scikit-learnClassificationRecommendation Engine

Hobbies & Interests

Life outside of building models and systems.

Writing for Towards Data Science

Writing for Towards Data Science

Sharing accessible data science insights and tutorials with the global TDS community.

Hiking

Hiking

Spending time off-grid, climbing peaks and exploring mountain trails across the continents.

Running & Fitness

Running & Fitness

Training for personal bests in running and the occasional endurance event.

Drawing & Painting

Drawing & Painting

Stepping away from the keyboard to work on charcoal sketching and oil painting.

Kayaking

Kayaking

Level 2 certified kayaker, getting out on the water to paddle across Ireland.

Backpacking

Backpacking

Travelling light from West to East to learn about new cultures and perspectives.