Ai Engineer – Totalenergies Digital Factory

AI Engineer

You will be integrated into the Data Science and AI team, an entity of about forty experts dedicated to the exploration, development, and deployment of data and AI solutions at the heart of the products that the Digital Factory delivers for the company's business areas.

The AI Engineer is responsible for:

• Industrialization and production of AI models
• Designing and evolving technical architectures for the deployment and operation of AI models
• Leading technical choices related to implementation (tools, frameworks, patterns)
• Anticipating performance, security, robustness, and maintainability constraints from the outset
• Ensuring the overall quality of AI components within their scope
• Having in-depth knowledge of cloud infrastructure and the deployment of AI-based products

Operation, reliability, and MLOps

• Defining, optimizing, and evolving MLOps pipelines (automation, advanced monitoring, retraining)
• Implementing advanced monitoring, alerting, and drift management mechanisms
• Taking operational responsibility for critical or large-scale AI systems
• Anticipating and addressing technical risks related to the operation of AI systems
• Ensuring the reliability, security, and scalability of AI solutions over time

Collaboration with product and technical teams

• Playing a key role in the framing and technical arbitration of AI use cases
• Leading technical exchanges with Data, IT, Product, and Platforms teams
• Contributing to structuring decisions related to architectures, tools, and modes of operation
• Ensuring technical coherence of deployed AI solutions

Standards, continuous improvement, and transmission

• Contributing actively to the definition and evolution of AI Engineering and MLOps standards
• Capitalizing on experience feedback and structuring best practices
• Accompanying the collective technical maturity increase
• Sharing expertise through mentoring, code review, and support for less experienced profiles
• Contributing to training, onboarding, and recruitment actions for AI technical profiles

Candidate Profile

Level of qualification:
Bachelor's degree/Master's or equivalent level in engineering school or applied mathematics, data science, AI.

Technical skills:

Experience in the design and development of Data/AI solutions and their deployment in production.

Mastery of a language:
Python required and Type Script is a plus.

Mastery of good software development practices (code quality, testing, documentation) to transform validated models into robust industrial solutions.

Ability to integrate and deploy artificial intelligence models into the information system in the form of services (API, batch, streaming), in connection with Data, IT, and Product teams.

Mastery of AI Engineering and MLOps practices (CI/CD, infrastructure, monitoring, incident management) to ensure the reliability, performance, and sustainability of AI systems in production.

Good knowledge of data and AI environments (e.g., Databricks) and cloud platforms (Azure and/or AWS), with an understanding of security, performance, and scalability issues.

Ability to apply and evolve AI Engineering and MLOps standards, capitalize on experience feedback, and contribute to the collective technical maturity increase.

Behavioral skills:
Teamwork, Communication, Ability to assert and say no when necessary, pedagogy, and ability to explain achievements to all types of audiences, curiosity, and proposal strength.

Language skills:
Fluent French & Practical English.

Certification:
Cloud certification is a plus (AWS or Azure).

Specific knowledge:
Experience in an industrial context is appreciated (logistics, inventory management, industrial maintenance, sensor data analysis, process analysis and modeling).

Experience level:
Minimum 8 years of experience in the development and deployment of ML models in production and more recently of generative AI in industrial projects.

Total Energies values diversity, promotes individual development, and offers equal employment opportunities to all candidates.