Quantitative / Machine Learning Engineer

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

Context & Environment

TotalEnergies is developing its activities across the power value chain, with a growing portfolio of renewable generation, flexible assets and power supply activities across Europe.

Within Trading & Shipping, our algorithmic trading teams are building advanced quantitative and machine-learning solutions to support trading and optimization activities in European short-term power markets.

As a Quantitative / Machine Learning Engineer, you will join a highly technical and collaborative environment at the intersection of energy trading, quantitative modelling, machine learning and software engineering.

You will contribute directly to the development of models and algorithms used to identify and capture opportunities in European power markets, working closely with quantitative analysts, algorithmic traders, data scientists and IT specialists.

The role offers significant exposure to fast-moving energy markets and the opportunity to work on models that move from research and back-testing through to live production and ultimately contribute to trading performance.

Activities

You have a strong quantitative background and enjoy applying advanced modelling techniques to complex, real-world problems.

We are looking for someone with:

• An engineering degree, Master's degree or PhD in a quantitative field such as Mathematics, Physics, Machine Learning, Computer Science or a related discipline.
• Approximately 2–3 years of professional experience working with machine-learning models in production, ideally involving live forecasting or other real-time applications.
• Strong proficiency in Python.
• Experience with MongoDB, SQL and Shell scripting.
• A solid understanding of software architecture and production-quality development practices.
• Experience with Docker and familiarity with DevOps/MLOps environments, including CI/CD pipelines.
• Strong knowledge of machine-learning techniques, including supervised and unsupervised learning.
• Practical experience with time-series modelling and analysis.
• The ability to analyse complex systems and identify direct and indirect relationships between multiple signals and datasets.
• Strong communication skills and the ability to explain quantitative results clearly to both technical and business stakeholders.
• The ability to work effectively in a fast-paced, collaborative trading environment.

Additional Assets

The following would be considered an advantage:

• Previous exposure to energy, commodities or financial markets.
• Understanding of European power markets, power generation or energy supply mechanisms.
• Experience working with trading signals, forecasting models or optimization problems.
• Familiarity with project-management and collaborative tools such as Jira, Asana or Monday.com.

Why Join Us?

This role offers the opportunity to work at the forefront of data science and algorithmic trading within the energy sector.

You will work on advanced quantitative models with a direct connection to live markets and trading decisions, while collaborating with experienced professionals across trading, quantitative research and technology.

You will join an international environment where machine learning and quantitative analysis play an increasingly important role in optimizing TotalEnergies' activities across European power markets.

Candidate Profile

As part of the Algorithmic Trading team, you will:

• Develop quantitative and machine-learning models supporting algorithmic trading strategies in European power markets.
• Build models across the full lifecycle, from data preparation and feature engineering through model training, optimization, validation and live deployment.
• Design new indicators, signals and features to improve quantitative and machine-learning trading models.
• Analyse large and complex datasets to identify patterns, relationships and trading signals.
• Conduct quantitative research on European power markets and translate market observations into actionable modelling ideas.
• Monitor the performance and robustness of models in both simulated and live trading environments.
• Continuously assess model behaviour and identify opportunities to improve forecasting accuracy and trading performance.
• Contribute to rigorous back-testing, validation and model-performance methodologies.
• Work with cross-functional teams to bring models into production and ensure their reliability, scalability and maintainability.
• Collaborate closely with algorithmic traders and technology teams to turn quantitative research into operational trading solutions.
• Contribute your data science expertise to broader modelling and optimization topics within the team.

Joining TotalEnergies means committing to the energy transition and helping provide energy that is more affordable, more available, and more sustainable for as many people as possible. You will grow within an international multi-energy company where every talent matters. You will contribute to ambitious projects and deliver concrete solutions to today's energy challenges.

Throughout your career, you will benefit from a wide variety of assignments and tailored learning opportunities. You will fully develop your potential in an environment that fosters innovation and excellence. Join committed and collaborative teams where success is built together.

We place respect and employee well-being at the heart of our performance. That is why TotalEnergies values diversity and promotes equal opportunities for all.