Open to opportunities

Matthieu Tohme

@matthieutohme

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Machine Learning graduate with expertise in building production-ready AI systems.

France

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What I'm looking for

I am looking for a dynamic work environment that fosters innovation and collaboration, where I can apply my skills in machine learning and software engineering while contributing to impactful projects.

I am a Machine Learning graduate from Imperial College London, specializing in building production-ready AI systems and advanced NLP research. My strong foundation in full-stack development allows me to create robust applications that leverage cutting-edge technologies. Currently, I am actively seeking opportunities to contribute to software engineering projects while applying for Master's programs in Machine Learning and Computational Engineering for the 2025-2026 academic year.

As the Founder and Full-Stack Developer at Forseen.io, I successfully created a prediction market platform from scratch, implementing an automated market-making algorithm and comprehensive risk management features. My experience at Le Wagon's Data Science & Engineering Bootcamp further honed my skills in building production ML pipelines and deploying models using Docker and Streamlit. I have a proven track record of enhancing data quality control systems during my internship at Société Générale, where I automated financial data processing workflows, significantly reducing manual processing time.

Experience

Work history, roles, and key accomplishments

Current

Founder & Full-Stack Developer

Current

Forseen.io

Jan 2025 - Present (7 months)

Created a prediction platform similar to Polymarket/Kalshi, enabling binary and multi-category options trading on real-world events. Implemented an automated market-making algorithm with synthetic liquidity, dynamic price adjustment, and real-time WebSocket integration for live trade execution.

fastAPI PostgreSQL Redis React Next.js Risk Management

Full-Stack Data Science

Le Wagon

Jul 2022 - Sep 2022 (2 months)

Built production-ready machine learning pipelines from data extraction to model deployment using Docker and Streamlit, incorporating MLOps practices and MLFlow monitoring. Implemented various supervised and unsupervised models, including deep learning solutions for NLP tasks.

Machine Learning Pipelines Docker Streamlit MLOps MLFlow Random Forest SVM Neural Networks TensorFlow Keras NLP

Software Engineering Intern

Société Générale

Jun 2018 - Jun 2018 (0 months)

Automated financial data processing workflows, which led to a 40% reduction in manual processing time. Enhanced data quality control systems for a macroeconomic research platform.

Workflow Automation Data Quality Software Engineering

Education

Degrees, certifications, and relevant coursework

Lycée Français Charles de Gaulle

French Baccalauréat, Mathematics

Grade: Highest Honors

Completed the French Baccalauréat with a specialization in Mathematics. Graduated with highest honors in the Scientific Stream.

Imperial College London

MSc Health Data Analytics & Machine Learning, Health Data Analytics & Machine Learning

Completed a Master of Science in Health Data Analytics & Machine Learning. Thesis focused on evaluating language models in scientific novelty detection, comparing GPT-4o/Phi-3 with traditional methods using PubMed abstracts. Applied advanced NLP techniques and statistical analysis.

King's College London

BSc Neuroscience, Neuroscience

Undertook a Bachelor of Science in Neuroscience. Led collaborative research initiatives, including investigations into post-herpetic neuralgia treatments. Applied computational methods to neuroscience research, focusing on bioinformatics and statistical analysis.