James Teversham
Applied AI at Mistral AI
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolJames Teversham is an Applied AI engineer with a decade of hands-on experience building production-grade ML and agentic systems across energy, finance, and supply chain domains. Trained in mechatronics and applied machine learning at Imperial College and UCT, he bridges mathematical rigour and systems engineering—designing digital twins, MPC controllers, and reinforcement-learning strategies that delivered measurable CapEx and OpEx savings for major utilities and trading businesses. He has shipped end-to-end platforms from embedded hardware and IoT for hydrogen systems to cloud-native ML pipelines using Vertex, MLflow, LangChain and LangGraph, and led projects that scale to tens of millions of multilingual reviews and real-time supply-chain monitoring. Pragmatic yet inquisitive, James pursues research interests in genetic algorithms, RL and robotics with an eye toward improving rural education and agricultural automation in South Africa. Notably, he combines deep theoretical grounding with a knack for turning simulations into stakeholder-facing dashboards and deployable controls.
10 years of coding experience
5 years of employment as a software developer
BSc Eng Mechatronics, Electrical and Electronics Engineering, BSc Eng Mechatronics, Electrical and Electronics Engineering at University of Cape TownMaster of Science - MSc, Applied Machine Learning, Master of Science - MSc, Applied Machine Learning at Imperial College LondonHigh School Diploma, High School Diploma at South African College School
Afrikaans, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (24)
toolbox9
digital-signal-processing9
parquet8
decoding8
java8
in-memory8
firmware7
micropython7
openmv7
esp326
apache-arrow6
esp82666
apache6
vector5
interchange5
Programming languages (5)
Github contributions (5)
iFix/jekyll-website2
Feb 2017 - Mar 2017
Contributions:67 PRs, 96 pushes, 15 branches in 16 days
JamesTev/EEG-decoding
Mar 2021 - Jan 2023
EEG decoding for an ultra low cost, real time BCI device based on the Espressif ESP32 running MicroPython.
Contributions:27 commits, 2 PRs, 54 pushes in 1 year 10 months
ccadigital-signal-processingdecodingbciesp8266
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