Aidan Dunlop


Software Engineer with over 7 years combined experience in ML, MLOps, software engineering, and AI Ethics.

Recently completed a first-class master’s degree in AI Ethics & Society at the University of Cambridge.

Looking to move into Responsible AI, combining my software engineering experience with my passion for AI Ethics.


Recent experience

Sky

Software Engineer, MLOps

Oct 2020 - Present

Building a platform for deploying ML models into production in a robust and scalable way, which enables recommendations to be served to millions of customers. Working on an open source custom Kubernetes operator for Kubeflow Pipelines. Using Go, Python, Scala, TensorFlow, TensorFlow Serving, TFX, Kubeflow, and gRPC.

Developer II

Mar 2020 - Oct 2020

Continued to strive for high quality production code whilst expanding the NOWTV application to more territories. Mentored junior developers, guided technical discussion, and established best engineering practices across teams.

Developer

Dec 2018 - Mar 2020

Developed and maintained NOW TV client applications for smart TVs and the web, enhancing features, fixing bugs, and optimizing CI pipelines. Led macOS notarization for Catalina compliance. Primarily worked with React/Redux.

Associate Software Developer

Jul 2017 - Dec 2018

Implemented a prototype Alexa skill/Google Home action, gaining experience with NodeJS and Alexa/Google Home APIs.

Summer Placement, Software Engineering Academy

Aug 2016 - Sep 2016

Education

University of Cambridge

MSt AI Ethics and Society

Sep 2021 - June 2023

1st Class part-time Master’s degree in AI Ethics and Society, equivalent to a full-time MPhil. A unique, multidisciplinary course that gave me the critical skills, knowledge, and analytical abilities needed to identify and address ethical challenges of AI. Dissertation on the ethical implications of open-source explainability tools.

Springboard

Machine Learning Engineering Career Track

Sep 2019 - May 2020

Intensive online course covering the fundamentals of machine learning, deep learning, NLP, and CV. Also involved a capstone project to design, develop and deploy a completely scalable machine learning system. Gained skills in Python, Scikit Learn, PyTorch, and end to end machine learning.

University of Manchester

BSc Computer Science

Sep 2014 - Jun 2017

1st Class BSc Computer Science (Hons). Overall grade: 79%. Third Year Project: 85%


Projects

  • Traffic Light Recognition: Detection of Traffic Lights using Faster RCNN architecture, written with Pytorch, deployed using AWS Elastic Beanstalk.
  • Tracking Football Players: Tracking football players in low quality video using traditional Computer Vision techniques.