Hi there. I am a freelance Software Engineer and host of the inside view podcast, where we talk about AI progress. I have previously worked with the number one french bank (working on a computer vision feature), hash.ai (working directly with the CEO on scaling), azmed.co (detecting bone fractures in X-rays with computer vision), ledr.io (building a Python/C API), FloydHub (wrote deep reinforcement learning blogs) and the Future of Humanity Institute (interned in AI Safety there). You can find some of my writing on FloydHub, Medium, the Alignment Forum and Twitter. I also sometimes mix and produce music.


Bank, Paris

Freelance Python developer

Implemented a new NLP feature for a chatbot. Currently developing the training pipeline, API and models for a Computer Vision module.

HASH, London

Right-hand of the CEO

Wrote scripts to automate hiring, emailing thousands of developers, defined our marketing and community building strategy, built financial model for our growth, financial operations, helped polish blogposts on multi-agent systems, wrote parsing scripts for competitive analysis.

AZmed, Paris

Deep Learning Researcher

AZmed is a company detecting bone fractures in X-rays using state-of-the art computer vision architectures. I pushed different ensembling of fine-tuned models to production, maximizing both sensitivity and specificity.

My main research contribution is an organ classifier, where I built a Graphical user interface to re-annotate data, re-annotated myself thousands of images from medical feedback, then automatically about one million medical images with 80% accuracy. This was then used to improve our pre-trainings.

LEDR, San Francisco (Remote)

Software Engineer

Wrote a wrapper in Python for a low-level network library in C and Ada. I then deployed this Python library to run predictions on time-series.

Future of Humanity Institute, Oxford

Deep Learning Internship

Open-sourced code for the paper "How useful is quantilization for mitigating specification-gaming?" by Ryan Carey. I worked on mathematical models for AI deception with Stuart Armstrong, work featured in the Alignment Newsletter.

FloydHub, San Francisco (Remote)

Deep Learning Writer

Wrote a "neat introduction to Reinforcement Learning" (creator of Keras) & 2nd top google search result on meta-reinforcement learning.


Simplified Experiments

Reproduced two experiments from Prefrontal Cortex as a Meta-Reinforcement Learning System by simplifying the observation and action space, bringing the training time from 112 GPU-days to 1 CPU-day.

Reinforcement Learning Book Challenge

Wrote the code from scratch for all of the models of "Reinforcement Learning: an Introduction", matching the peformance of the 47 experiments. The repo includes the solution for all of the exercises, anki flashcards summarizing the core concepts in the book and my code for all of the experiments.