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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.
Job Responsibility:
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
Requirements:
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 a at least two mainstream programming language (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