Senior AI/ML Engineer — Pipelines & MLOps (Azure)

EcoVadis; Warszawa; Hybrid; PLN 240,000 - 360,000; Full time

Benefits offered by this job

Hybrid work in Warsaw

Wellness allowance

L&D opportunities

Health insurance

Multisport card

Lunch card

Flexible working hours

Job summary

EcoVadis is seeking a Senior AI/ML Engineer to join our growing AI Center of Excellence. You will drive innovation by building scalable AI/ML systems, pipelines, and infrastructure, enabling cross-functional teams to leverage data-driven insights.

You will work with Python, MLflow, Azure stack, and Databricks, collaborating with scientists and engineers to deploy end-to-end ML solutions in a dynamic, international environment.

Qualifications

• Degree in Computer Science, Mathematics, Engineering, or a related technical discipline.
• Experience in driving, designing and implementing production-grade AI/ML systems and integrating into business applications.
• Strong programming skills in Python and ML libraries.
• Experience with MLOps / LLMOps / AgentOps tooling and lifecycle concepts.

Responsibilities

• Leverage data to solve business problems across EcoVadis.
• Design, develop, deploy and maintain scalable AI/ML systems.
• Design AI/ML pipelines applying MLOps / LLMOps / AgentOps best practices.
• Build AI/ML engineering infrastructure to orchestrate batch and real-time pipelines.
• Run large-scale experiments to ensure quality and efficiency of ML/data pipelines.
• Partner with scientists and engineers to make AI/ML models accessible to end-users.

Skills

Communication

Critical thinking

Analytical skills

Cross-functional collaboration

Python programming

Education

Degree in Computer Science / Mathematics / Engineering

Tools

MLflow

LangChain

VectorDBs

Azure

AzureML

Databricks

Docker

Job description

EcoVadis is seeking a Senior AI/ML Engineer to join our growing AI Center of Excellence. You will drive innovation by building scalable AI/ML systems, pipelines, and infrastructure, enabling cross-functional teams to leverage data-driven insights.

You will work with Python, MLflow, Azure stack, and Databricks, collaborating with scientists and engineers to deploy end-to-end ML solutions in a dynamic, international environment.