AI Azure ML Engineer

NTT DATA Europe & Latam; Emilia-Romagna; In loco; EUR 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

NTT DATA Europe & Latam is seeking an experienced ML/AI Architect to design and deploy AI solutions on Microsoft Azure, covering data ingestion, feature engineering and model training. You will implement MLOps, CI/CD pipelines, and operational monitoring to keep AI systems reliable, scalable and secure, while optimizing costs and performance.

Collaborating with data engineers, software developers and business stakeholders, you will deliver enterprise-grade data platforms and AI capabilities that

Competenze

• Bachelor’s degree in Computer Science, Informatics, Engineering or equivalent practical experience.
• Minimum 5+ years in ML/AI-focused roles.
• Strong experience designing and deploying AI/ML solutions on Microsoft Azure.
• Solid understanding of end-to-end ML pipelines and MLOps concepts.
• Hands-on with CI/CD pipelines and production monitoring for AI systems.
• Expertise in data preprocessing, feature engineering and data quality assurance.
• Practical knowledge of vector databases, embeddings, and retrieval-based AI systems.
• Experience evaluating and selecting ML frameworks and tooling based on use case needs.
• Good awareness of security, cost optimization, and performance considerations in cloud-native AI solutions.
• Excellent verbal and written communication skills in English.

Mansioni

• Architect and deploy AI solutions using Microsoft Azure services.
• Design end-to-end AI/ML architectures covering data ingestion, feature engineering, model training, deployment, and monitoring.
• Implement MLOps practices, including CI/CD pipelines and operational monitoring.
• Preprocess and analyze data to ensure high-quality inputs for AI and retrieval-based systems.
• Create and manage vector indexes to support AI search and retrieval use cases.
• Evaluate, select, and integrate appropriate ML frameworks, tools, and platforms.
• Ensure AI solutions comply with security, cost, and performance standards.

Conoscenze

AI/ML architecture design

Microsoft Azure

MLOps

CI/CD pipelines

Data preprocessing

Feature engineering

Data quality assurance

Vector databases

Embeddings

Retrieval-based AI

Security & cost optimization

Performance optimization

Communication skills

Formazione

Bachelor’s degree in Computer Science, Informatics, Engineering

Strumenti

CI/CD tooling

Azure services (general)

Descrizione del lavoro

Who We Are

We operate beyond organizational silos, combining deep expertise in data engineering and AI-driven solutions to design and deliver scalable, user-centric applications and modern data architectures. We support a wide range of industries, including Automotive, Banking, Insurance, Telecommunications, E-commerce, and Public Services. Our focus is on building robust, enterprise-grade data platforms and enabling advanced analytics and AI capabilities within the Microsoft ecosystem, including Azure, Microsoft Fabric, and the Power Platform. We specialize in designing secure, high-performance solutions that integrate data pipelines, AI models, and Generative AI use cases to deliver real business value.

What You’ll Be Doing

• Architect and deploy AI solutions using Microsoft Azure services.
• Design end-to-end AI/ML architectures covering data ingestion, feature engineering, model training, deployment, and monitoring.
• Implement MLOps practices, including CI/CD pipelines and operational monitoring.
• Preprocess and analyze data to ensure high-quality inputs for AI and retrieval-based systems.
• Create and manage vector indexes to support AI search and retrieval use cases.
• Evaluate, select, and integrate appropriate ML frameworks, tools, and platforms.
• Ensure AI solutions comply with security, cost, and performance standards.

What You Bring Along

• Bachelor’s degree in Computer Science, Informatics, Engineering, or equivalent practical experience
• Minimum 5+ years of experience ML and AI-focused roles
• Strong experience designing and deploying AI/ML solutions on Microsoft Azure.
• Solid understanding of end-to-end ML pipelines and MLOps concepts.
• Hands-on experience with CI/CD pipelines and production monitoring for AI systems.
• Expertise in data preprocessing, feature engineering, and data quality assurance.
• Practical knowledge of vector databases, embeddings, and retrieval-based AI systems.
• Experience evaluating and selecting ML frameworks and tooling based on use case needs.
• Good awareness of security, cost optimization, and performance considerations in cloud-native AI solutions.
• Excellent verbal and written communication skills in English