ML Engineer
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I am enthusiastic about data, and when solving problems I get stuck in and work closely with the people around me to get to the solution.
As a developer, I have a foundation in essential concepts such as version control, CI/CD, unit testing and ML Ops, as well as cloud computing and containerised solutions such as AWS and Docker. On the ML side, I have strong skills in the fundamental data science libraries, as well as experience with ML frameworks including sklearn, Huggingface and PyTorch. I have used all of these skills to build end-to-end ML pipelines from data gathering using SQL with Snowflake, EDA, model optimisation and deployment to production - becoming a reliable developer of ML solutions.
I have a Distinction in MSc Ecological Applications from Imperial College London where I completed a Data Science thesis on UK pollinators
