ML Engineer Senior - GenAI Solutions

Overview

As 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.

Responsabilità Apply 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 fondamentali 5+ 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