Energy Trading ML Engineer: Quantitative Modeling

TotalEnergies Trading; Genf; On-site; CHF 120,000 - 180,000; Full time

Job summary

TotalEnergies Trading in Geneva seeks a Quantitative / Machine Learning Engineer to join our algorithmic trading teams. You will develop models and algorithms across the energy markets, moving from research and back-testing to live production and trading decisions.

You will collaborate with quantitative analysts, traders, data scientists and IT specialists, applying advanced modelling, time-series analysis and ML techniques in a fast-paced environment.

Qualifications

• Engineering degree or higher in Mathematics, Physics, ML, CS or related field.
• 2–3 years of professional experience with ML models in production.
• Strong proficiency in Python and data processing.
• Experience with MongoDB/SQL and shell scripting.
• Familiarity with Docker and CI/CD pipelines.
• Knowledge of time-series modelling and forecasting.
• Ability to communicate quantitative results to both technical and business stakeholders.

Responsibilities

• Develop quantitative and ML models supporting algorithmic trading in European power markets.
• Build models through data prep, feature engineering, training, validation and live deployment.
• Design indicators and signals to improve trading models.
• Analyze large datasets to identify patterns and trading signals.
• Collaborate with traders, quants and IT to productionise models.
• Contribute to back-testing, validation and model-performance methodologies.
• Ensure model reliability, scalability and maintainability in production.

Skills

Python

Time-series modelling

Machine learning

Production ML

Education

Engineering/ MSc/ PhD in a quantitative field

Tools

MongoDB

SQL

Shell scripting

Docker

Jira

Asana

Monday.com

Job description

TotalEnergies Trading in Geneva seeks a Quantitative / Machine Learning Engineer to join our algorithmic trading teams. You will develop models and algorithms across the energy markets, moving from research and back-testing to live production and trading decisions.

You will collaborate with quantitative analysts, traders, data scientists and IT specialists, applying advanced modelling, time-series analysis and ML techniques in a fast-paced environment.