Senior AI/ML Engineer

EcoVadis

24d•Hybrid

About The Position

EcoVadis is seeking a Senior AI/ML Engineer to join its growing AI Center of Excellence and use artificial intelligence and machine learning to drive innovation across the organization. The role uses data to address business problems across EcoVadis business units and involves designing, developing, deploying, and maintaining scalable AI/ML systems. The engineer will create AI/ML pipelines using MLOps, LLMOps, and AgentOps best practices; build infrastructure to orchestrate batch and real-time pipelines; and run large-scale experiments and tests to ensure the quality and efficiency of machine-learning and data pipelines. The role also partners with scientists and engineers to make models accessible to end users and downstream processes. Solutions are developed using Python, MLflow, the Azure ecosystem, and Databricks. The position is available as hybrid work in Barcelona, with two days per week in the office, or fully remote from Spain. EcoVadis describes itself as a provider of business sustainability ratings, using data and technology to provide companies with insights into environmental, social, and ethical risks.

Requirements

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 ML libraries.
Strong experience with the AI/ML lifecycle, its principles, and MLOps, LLMOps, or AgentOps tooling.
Experience with cloud technology and Databricks; Azure experience is preferred.
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 ML 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, for example with engineers and product managers.
Outgoing personality, drive, and interest in an international and dynamic work environment.
Excellent verbal and written communication, critical-thinking, and analytical skills.

Nice To Haves

Experience with Azure ecosystem tools such as Azure Foundry, Azure Bicep, Azure ML, and Azure Cloud Storage.
Familiarity with tools such as MLflow, LangChain, vector databases, and evaluation frameworks.
Contributions to open-source libraries.

Responsibilities

Use data to solve business problems for various EcoVadis business units.
Design, develop, deploy, and maintain scalable AI/ML systems.
Design AI/ML pipelines using MLOps, LLMOps, and AgentOps best practices.
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 ML and data pipelines.
Partner with scientists and engineers to make AI/ML models accessible to end users and downstream processes.
Deliver end-to-end solutions using Python, MLflow, the Azure ecosystem, and Databricks.