Samuel Lynn-evans is a Senior Data Engineer with nine years of experience building data platforms and ML tooling across fintech and AI startups in the UK. Currently at AutogenAI after senior data-engineering roles at ClearScore and Skyscanner, he combines production-grade data engineering with hands-on machine learning work—authoring a Transformer seq2seq implementation that demonstrates deep familiarity with attention mechanisms, tokenizers and PyTorch. He writes about AI for technical audiences and teaches coding through Code at Uni, reflecting a knack for translating complex concepts into practical learning. A graduate of Ecole 42 with a BSc in Molecular Biology, he brings an autodidactic mindset and cross-disciplinary curiosity that inform pragmatic, research-aware engineering. Outside the office he has funded his studies through SEO copywriting and even managed organic vegetable production, underscoring a resourceful, results-oriented approach.
9 years of coding experience
5 years of employment as a software developer
BsC, Molecular Biology, BsC, Molecular Biology at University of Bristol
Transformer seq2seq model, program that can build a language translator from parallel corpus
Role in this project:
ML Engineer
Contributions:27 commits, 2 PRs, 33 pushes in 11 months
Contributions summary:Samuel primarily worked on a transformer sequence-to-sequence model for language translation, likely building a program to translate between different languages. The commits show implementation of core components like embeddings, positional encoding, multi-head attention and feed forward networks and the integration of various libraries like PyTorch and TorchText. The user was involved in setting up the data pipeline using the tokenizers, building vocabularies and pre-processing data.
Contributions:11 commits, 20 pushes, 1 branch in 3 months
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