Resume
Relevant Experience
2023 -
Canva, Machine Learning Engineer
On the Visual AI Platform team.
2021 - 2023
EODC, Software Developer
Worked with (big) satellite imagery.
Wrote & maintained a backend + REST API for on-demand Earth Observation data processing using Python.
I also setup and nurtured the underlying Kubernetes cluster and practised CI/CD, GitOps, Devcontainers
and Infrastructure-as-Code to stay sane.
2020 - 2021
Research Sabbatical
Took some self-funded time off to figure out what I want to do next. I ended up wildly studying lots of
different things in math, history & philosophy that I didn't have time for before.
Tech projects I worked on:
- Built codeatlas.dev, a codebase visualisation tool
- Created a habit-tracking Slack bot for myself
- Worked through the fastai course
2018 - 2020
Echobox, Data Scientist
I was responsible for developing, testing, deploying and monitoring machine learning models for a wide
variety of use-cases, e.g. scoring, classification and clustering tasks.
2016 - 2017
University College London, Research Assistant
Text-mining a large database of apps to detect free/premium versions of the same app.
Work supervised by Dr. Yongdong Liu.
Academia
2021 - 2021
Started a PhD in Computer Science, realized it wasn't for me and moved on.
2017 - 2018
MSc Artificial Intelligence, University of St Andrews
Graduated with Distinction.
Courses on Machine Learning, Search, Logic, Distributed Systems, Software Engineering, Natural Language Processing and Human-Computer Interaction. Master thesis on teaching a virtual robot to juggle.
Courses on Machine Learning, Search, Logic, Distributed Systems, Software Engineering, Natural Language Processing and Human-Computer Interaction. Master thesis on teaching a virtual robot to juggle.
2014 - 2017
BSc Management Science, University College London
First Class Honours.
Courses on Data Analytics, Algorithms, Machine Learning, Linear Algebra, Calculus, Probability & Statistics, Microeconomics & Game Theory, Finance, Behavioural Science, Design and Decision Theory.
Courses on Data Analytics, Algorithms, Machine Learning, Linear Algebra, Calculus, Probability & Statistics, Microeconomics & Game Theory, Finance, Behavioural Science, Design and Decision Theory.
Tech Stack in approximate order of expertise
- Languages & Frameworks: Python (numpy, pandas, PyTorch, fastai, jupyter, SpaCy, sklearn, dask), Java, Javascript/Typescript (React)
- Machine Learning: Deep Learning (+ many of its modern flavours), NLP, Reinforcement Learning, Genetic Algorithms, Computer Vision, clustering, dimensionality reduction
- Tools: git, CI/CD enthusiast, Docker, Kubernetes