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Veolia

Water, waste, and energy services provider

AI Engineer

Applied Machine LearningPosted on Nov 10
Full-timeSaint-Maurice, France€40k - €55k /yr

About the Job

Requirements

  • Translate business needs into performant AI architectures and develop and deploy robust, scalable AI models and agents in production.
  • Supervise production solutions and support continuous improvement while ensuring compliance, traceability, and security of AI assets, including the AI Act and GDPR.
  • Maintain active technology awareness to identify relevant advances in machine learning and large language models.
  • Design reliable, documented solutions and critically assess technical choices.
  • Take ownership of projects from end to end and adapt to technological changes.
  • Collaborate effectively with business and technology teams and justify architectural choices.

Responsibilities

  • Design and industrialize AI solutions by translating business needs into robust models and applications, from experimentation through production deployment.
  • Ensure the reliability of AI assets by maintaining data quality, performance, security, and maintainability.
  • Industrialize AI agents by designing reliable, secure, and scalable solutions from experimentation through production deployment.
  • Use and extend the Veolia agentic stack (VSG) to integrate agents into existing processes.
  • Develop and deploy machine-learning models while ensuring data quality, performance, robustness, and model monitoring.
  • Document data, models, and uses to ensure traceability and compliance with AI Act requirements.
  • Understand business-team needs and contribute to AI solution design by assessing feasibility, relevance, and potential value.
  • Contribute to architecture and technology choices, assessing cloud services such as GCP and AWS, internal components, and custom development.
  • Build rapid prototypes to test ideas and validate their value before industrializing them.
  • Develop and evaluate machine-learning models, generative AI solutions, and intelligent agents, including prompts, workflows, tools, integrations, and knowledge bases.
  • Automate testing, versioning, and deployments using existing tools to turn prototypes into robust, maintainable, scalable production solutions.
  • Monitor deployed solutions, including response quality, latency, availability, costs, and model drift; manage incidents, changes, and continuous improvement.
  • Track developments in machine learning, large language models, AI agents, frameworks, architectures, MLOps, and LLMOps.
  • Test and evaluate emerging technologies through prototypes and benchmarks, considering practical value, performance, cost, integration ease, and risks.
  • Identify innovation opportunities and propose improvements to products, processes, and the existing AI stack.
  • Share knowledge and experience with teams, contribute to documentation and technical standards, and promote good practices.
  • Ensure data, model, and agent quality, traceability, and governance by documenting use cases, risks, evaluations, and lifecycle decisions.
  • Secure AI solutions by protecting access, data, tools, and agent-executed actions, while following the AI Act, GDPR, security policies, and internal rules.
  • Contribute to the organization's AI asset portfolio by helping structure, monitor, and continuously improve it.

About the Company

Veolia

Water, waste, and energy services provider

Generating company summary.

Company size
10,001+
Company stage
IPO
Headquarters
Aubervilliers, France
Founded
1853

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