ML Engineer Senior - GenAI Solutions

Experteer Overview

As a Senior Machine Learning Engineer at NTT DATA, you will collaborate with Data Scientists and ML Engineers on advanced ML and Generative AI initiatives. You will implement GenAI capabilities across cloud (Azure/GCP) and on‑prem architectures, build scalable data pipelines, and drive production ML solutions. You will mentor teammates, engage stakeholders, and manage multiple projects to deliver impactful AI-driven outcomes for clients. This role offers hands‑on impact in shaping GenAI deployments and data‑driven decision making within a global tech services environment.Retribuzione / Benefits

• Apply hands‑on Generative AI capabilities across Azure/GCP and on‑prem GenAI architectures and MLOps
• Leverage a strong mathematical background to solve complex problems
• Tackle classification, information retrieval, clustering and optimization tasks
• Establish scalable, automated processes for large-scale data analysis
• Contribute to model development, validation and implementation
• Identify business opportunities through ML initiatives
• Design and build data pipelines from experiments to production
• Manage multiple projects and lead ML Engineers
• Engage with stakeholders to align ML work with business goals

Responsabilità

• At least 5 years of production experience in Data Science or Software Engineering
• Strong knowledge of mathematics, probability, statistics and algorithms
• At least 6–12 months of Generative AI deployment experience
• Vector database knowledge is a plus
• Understanding of data structures, data modeling and software architecture
• Fluent in at least two mainstream programming languages (Python, Scala, Java, C++)
• Experience building infrastructure for technical users (DS, ML practitioners, data consumers/producers)
• Knowledge of Spark and Databricks is a strong plus
• Experience deploying ML solutions in cloud and cross-cloud environments; Snowflake knowledge is a plus
• Proficiency with ML frameworks (Keras, PyTorch)
• Ability to design/implement production ML pipelines; familiarity with CI/CD, containerization and MLops concepts
• Ability to mentor junior team members and build relationships with clients and teammates

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