Senior Machine Learning – Software Developer

Total Energies


Country
Switzerland

Location
Switzerland

Workplace location
GENEVE-WTC1(CHE)

Employer company
TotalEnergies Gas & Power Ltd

Domain
Governance and Information, Information Systems, Strategy Economics Business

Type of contract
Regular position

Experience
Minimum 6 years

Candidate Profile

    • You are a talented individual with a strong technical or engineering background. A PhD in Mathematics, Physics, Machine Learning, or Computer Science is an advantage.
    • You are a continuous learner with a strong team spirit, always seeking to improve and innovate beyond the status quo.
    • You have solid skills in machine learning, software engineering, and data science. 
    • You have 5+ years of successful experience in software development or maintenance, with a proven track record of working with large frameworks and code-bases. Must be able to write scalable, well-tested and well-documented code that adheres to best practices and is prepared for future use cases.
    • You show a strong understanding of ML techniques and paradigms, including expertise in feature engineering, model generalization, and mitigation of overfitting. Demonstrated experience with a diverse array of ML algorithms, such as decision trees (e.g., XGBoost, LightGBM, Scikit-learn) and neural networks (e.g., Keras, PyTorch).
    • You have experience in deploying ML models in production environments.
    • Proficiency in Python, MongoDB, and Shell scripting.
    • Familiarity with DevOps/MLOps best practices, CI/CD, and Docker.
    • You show clear and effective communication skills for reporting and collaboration. 
    • Language Skills : Fluent in English or French native/fluent speaker with an advanced English level. 
  •  

    Additional and advantageous requirements:

  • Familiarity with cloud systems

  • Experience with time-series analysis and forecasting is a plus.

  • Familiarity with the energy and commodities markets is beneficial.


 If this sounds like you, don’t wait any longer and Apply!

At TotalEnergies, we believe that our employees’ fulfilment has its roots in the wealth of the experiences they are offered. We are an equal opportunity employer committed to respecting diversity and inclusion in the workplace.
Applicants will receive consideration for employment without regard for race, color, gender, religion, national origin, disability, military status, age, marital status, sexual orientation, gender identity, genetic information or any other protected group status.
 

 

Activities

Are you looking to grow your career in the vibrant world of Power trading?
 Do you have solid skills in Machine Learning coupled with software engineering and Data science?

If yes, we would love to see your profile!

 

About us
 
We are looking to hire our new Senior ML – Software Developer, reporting to our Lead Predictive Product Development and Innovation, to join our Performance team which is part of the Predictive Department of TotalEnergies Gas & Power (TEGP). 

 

TotalEnergies Gas and Power is the trading arm of TotalEnergies in the field of low carbon energies (mainly gas, LNG and power). As such it operates in fast-evolving market dynamics influenced by internal and external factors that require constant adaptation and evolution. 

Uncertainties specific to the trading environment (volatility of prices, supply & demand mismatches) are coupled with those coming from the broader energy sector (climate change policies, changes in the energy mix, developments of new energy sources, etc). In such context Trading helps to ensure growth and profitability to a key segment of the business in order to reach the objective of Carbon Neutrality by 2050.

 


What you will do

As part of the Predictive Product Development and Innovation Team, you will be at the forefront of development of the Predictive Department Auto-ML libraries, responsible for performant and efficient execution of all phases of production-grade ML from data input to live result delivery, including feature engineering, data optimization, model tuning, results delivery, performance monitoring, and continuous improvement.

You will develop and maintain scalable, production-ready Auto-ML python libraries for time-series forecasting, ensuring they are optimized for performance, automation and ease of use.

You will create accompanying libraries such as for automatic portfolio optimization, robust monitoring and extensive interactive visualization (streamlit, dash, etc.) to facilitate user understanding and interaction with the forecasting models. 

You will test and integrate advanced modeling techniques, with a focus on continuous improvement.

You will oversee the frameworks, monitor performance (both in terms of results and computational efficiency), and proactively implement enhancements based on analytical findings.

You will also provide expert support to data scientists from the Energy Forecasting Strategy team developing models for trading-related use cases by leveraging your comprehensive understanding of the Predictive Department libraries. You will facilitate their work by clearly presenting the libraries’ features and guiding them to fully utilize the capabilities of the frameworks, ensuring they can maximize the potential of their models.

Collaborating with the MLOps team, you will establish robust automatic pipelines to ensure smooth delivery of forecasting products.

Context & Environment

  • PurposeThe Predictive Department is at the forefront of leveraging machine learning to provide valuable insights for various trading desks, propelling the efficiency of the energy transition. It will become the center of competence for Data science / ML for Gas & Power Trading
  • Objectives: Develop and maintain advanced, in-house Auto-ML forecasting libraries and data analytics frameworks specifically tailored for energy management, optimization, and trading. Central to the team’s expertise is Auto-ML for time-series, which guarantees that the AI models effectively address the complex challenges such as pricing, hedging, trading, transactions, and asset management. The team comprises highly skilled data scientists, software engineers, data architects, and ML-ops engineers.
  • ImpactThe role directly affects TGP’s trading performance by delivering accurate market forecasts. The job holder will collaborate with the Energy Forecasting Strategy and MLOps teams to deliver production-ready ML models with clear, actionable insights. Such a role demands strong technical skills, critical thinking and a team spirit.
  • Location: Based in Geneva, the incumbent will develop software crucial for forecasting market trends across all commodities traded by TGP, including global gas, LNG, electricity, emissions, dry products, and more.
  • Contribution: The forecasts generated by the Auto-ML libraries are expected to significantly impact the P&L for Power Trading, contributing approximately $1 billion/year across various geographies and trading activities such as Asset, Prop Trading, Structured Portfolio, Short Term Power, Origination, and New Ventures.

To apply for this job please visit totalenergies.avature.net.