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EcoVadis

Global sustainability ratings for supplier risk

Senior AI/ML Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A degree in Computer Science, Mathematics, Engineering, or a related technical discipline.
  • Industry experience driving, designing, and implementing production-grade AI/ML systems, integrating them into business applications, and monitoring models at scale.
  • Strong programming skills in Python and related machine learning libraries.
  • Strong experience with the AI/ML lifecycle, principles, and MLOps, LLMOps, or AgentOps tooling, such as MLflow, LangChain, vector databases, and evaluation frameworks.
  • Experience with cloud technology, preferably Azure and its ecosystem, including Azure Foundry, Azure Bicep, Azure ML, and Azure Cloud Storage, as well as Databricks.
  • A solid understanding of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
  • Experience with REST APIs for machine learning model serving.
  • Experience with Docker and container orchestration.
  • Experience with relational and non-relational databases.
  • Experience collaborating cross-functionally on AI/ML products and services with engineers, product managers, and others.

Responsibilities

  • Leverage data to solve business problems across various business units.
  • Design, develop, deploy, and maintain scalable AI/ML systems.
  • Design AI/ML pipelines using best practices in MLOps, LLMOps, and AgentOps.
  • Build AI/ML engineering infrastructure and systems to orchestrate batch and real-time pipelines.
  • Run large-scale experiments and tests to ensure the quality and efficiency of machine learning and data pipelines.
  • Partner with scientists and engineers to make AI/ML models accessible to end users and downstream processes.
  • Use Python, MLflow, the Azure stack, and Databricks to deliver end-to-end solutions.

Desired Qualifications

  • Contribution to open-source libraries is a plus.

About the Company

EcoVadis

Global sustainability ratings for supplier risk

EcoVadis operates a global sustainability ratings platform that helps companies assess and improve environmental and social performance. It uses a single universal scorecard and benchmarking framework on a shared platform, where data is analyzed against standardized criteria to generate scores and improvement recommendations, and it offers tools for supplier collaboration and evaluation. IQ Plus adds risk-intelligence screening for companies. Its goal is to help organizations manage ESG risk, meet investor and regulatory expectations, and build responsible, sustainable supply chains.

Company size
1,001-5,000
Company stage
Series C
Total funding
$736.9M
Headquarters
Paris, France
Founded
2007

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