Jonas Vetterle

I’m a Machine Learning engineer, technologist and former econometrician, but most of all: a builder! Having worked in start-ups and scale-ups, I’ve lived through some of the ups and downs of early-stage companies. I have huge respect for anyone taking the risk of building their own company and am always open to brainstorm tech, anything AI-related in particular, and be helpful where I can.

At Moonfire, I’m responsible for most of our backend. This ranges from building out ingestion pipelines for our raw data, all the way to training and deploying Machine Learning models. At the early stage of the VC cycle we operate in, we’re dealing with a lot of textual data. Fortunately, that aligns perfectly with my passion for NLP and also means we can take full advantage of the current wave of LLM-related technological advances.

Prior to Moonfire, I worked at Benevolent AI on the NLP team. There, I trained and deployed transformer-based NLP systems for interesting tasks like Named Entity Recognition, Entity Linking and Relationship Extraction on biomedical text. Before that, I worked at AI startup Kortical where I spent 3 years helping to build a machine learning SaaS product with a heavy focus on NLP. In what feels like a lifetime ago, I worked as an Economist at Frontier Economics in London, Spain and Germany, where I worked with the European Investment Bank, Deutsche Telekom and the London Stock Exchange.

I’m all about lifelong learning. Be it in terms of formal education (I earned a MSc in Economics with Distinction from LSE and a MSc Machine Learning with Distinction and a spot on the Dean’s List 2016-17 from UCL) or teaching myself to code. Machine Learning and AI began as a hobby for me and turned into a new career entirely and I continuously read papers to keep up with the cutting edge. I’ve also spent the last 4 years learning about Quantum Computing in my free time, and I can’t wait for a large-scale (and less noisy) quantum computer to arrive!