Ml Engineer Senior - Genai Solutions
Pubblicato il 14-09-2026 - Ntt Data in Bari
OverviewAs a Senior ML Engineer at NTT DATA, you will collaborate with data scientists and ML engineers on advanced Generative AI initiatives.
You apply hands-on GenAI capabilities across cloud and on-prem architectures, shaping scalable data pipelines and automated processes.
You will lead model development, validation, and production deployment while identifying business opportunities.
This role sits at the intersection of data, software, and client engagement, offering a chance to mentor colleagues and influence cross-functional projects.
ResponsabilitàApply Generative AI capabilities in cloud (Azure/GCP) and on-prem GenAI architectures and MLOps
Work on classification, information retrieval, clustering and optimization problems
Build scalable, automated data analysis processes for large-scale data
Contribute to model development, validation and production implementation
Identify business opportunities and connect with stakeholders
Design and create data pipelines from experiments to production
Manage multiple projects and lead ML Engineers
Requisiti fondamentali5+ years of production experience in Data Science or Software Engineering
Solid foundation in math, probability, statistics and algorithms
6–12 months of Generative AI deployment experience and underlying architecture
Vector Database knowledge is a plus
Understanding of data structures, data modeling and software architecture
Fluent in at least two programming languages among Python, Scala, Java, C++
Experience building infrastructure for data scientists/ML practitioners
Strong knowledge of Spark; Databricks is a plus
Experience deploying ML solutions in cloud and cross-cloud environments; Snowflake knowledge is a plus
Deep knowledge of ML frameworks (Keras, PyTorch)
Ability to design/implement production ML pipelines; familiarity with CI/CD, containerization, and MLops/Re-Training/Drift Management
Ability to mentor junior team members and maintain relationships with teams and clients
leadership and mentoring
stakeholder management
cross-functional collaboration
Generative AI deployment
Azure and Google Cloud Platform (GCP)
on-prem GenAI architectures