ML Engineer Senior - GenAI Solutions

NTT DATA Europe & Latam; Bari; On-site; EUR 90,000 - 120,000; Full time

Job summary

NTT DATA Europe & Latam seeks a Senior Machine Learning Engineer to collaborate with Data Scientists and ML Engineers on cutting-edge ML and Generative AI initiatives across multiple contexts. The role involves building and deploying scalable data pipelines, and leading ML practitioners to deliver production-grade solutions.

Ideal candidates bring deep math, extensive production experience in DS/SE, and hands-on GenAI deployment across cloud and on-prem architectures, with strong collaboration

Qualifications

• Minimum 5 years of production experience in Data Science or Software Engineering.
• Strong background in mathematics, probability, statistics and algorithms.
• Experience deploying Generative AI for production environments (≥6–12 months).
• Vector database knowledge is a plus.
• Understanding of data structures, data modeling and software architecture.

Responsibilities

• Apply hands-on Generative AI capabilities, preferably on Azure/GCP and on-prem GenAI architectures and MLOps.
• Leverage a strong mathematical background.
• Work on classification, information retrieval, clustering and optimization problems.
• Establish scalable, efficient and automated processes for large-scale data analysis.
• Contribute to model development, validation and implementation.
• Identify business opportunities.
• Design and create new data pipelines from scratch, from experiments to production deployment.
• Manage multiple projects.
• Lead ML Engineers.
• Connect with stakeholders.

Skills

Generative AI deployment

Data science

Python

Scala

Java

C++

Spark

Databricks

Snowflake

Keras/PyTorch

MLOps

CI/CD

Production ML pipelines

Mentoring juniors

Stakeholder management

Vector database

Cloud platforms

Tools

Spark

Databricks

Snowflake

Keras

PyTorch

Job description

As a Senior Machine Learning Engineer at NTT DATA, you will work alongside experienced Data Scientists, Data and ML Engineers on advanced machine learning and Generative AI initiatives.

Your Contribution In This Role

• Apply hands‑on Generative AI capabilities, preferably on Azure/GCP and on‑premise GenAI architectures and MLOps
• Leverage a strong mathematical background
• Work on classification, information retrieval, clustering and optimization problems
• Establish scalable, efficient and automated processes for large‑scale data analysis
• Contribute to model development, model validation and model implementation
• Identify business opportunities
• Design and create new data pipelines from scratch, from experiments to production deployment
• Manage multiple projects
• Lead ML Engineers
• Connect with stakeholders

The ideal profile

• At least 5 years of production experience working in Data Science or Software Engineering;
• Deep knowledge of math, probability, statistics and algorithms;
• At least 6/12 months of experience in Generative AI deployment and underlying architecture handling;
• Vector Database knowledge is well appreciated;
• Understanding of data structures, data modeling and software architecture;
• Fluent in at least two mainstream programming languages (Python, Scala, Java, C++);
• Experience in building an infrastructure for technical users, such as Data Scientist, ML practitioners or data consumers/producers;
• Strong knowledge of Spark, Databricks is a strong plus;
• Experience developing/deploying ML solutions in one of the public cloud platforms and on a cross‑cloud base, Snowflake knowledge is a plus;
• Deep knowledge with machine learning frameworks (such as Keras or PyTorch);
• Ability to design and implement machine learning pipelines in a production environment;
• Experience with deployment including knowledge of CI/CD, containerization, and related concepts with a focus over MLOps/Re‑Training/Drift Management;
• Ability to train more junior team members in multiple Machine Learning and Deep Learning concepts;
• Establish and maintain strong relationships with internal team members and external clients

Location

Milano, Bari, Bologna, Cosenza, Napoli, Pisa, Roma, Torino