Experteer 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
Experteer 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
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
Initial Contract lenght: 6 months (possible extensions based on performance) Job type: Hybrid, Full remote Requisites Knowledge of K8s architecture Configuration resources: StatefulSet, Deployments, Services, Ingress, ConfigMap, Job/CronJob Secrets management (e.g. Sealed Secret Operator) and environment
NTT DATA Europe & Latam is seeking a Senior Data Scientist to contribute to diverse projects involving Generative AI and machine learning solutions. The successful candidate will collaborate with various stakeholders, ensuring high-quality project execution. This role
Key Responsibilities Solution Design & Implementation: Lead the analysis, design, and implementation of Murex modules related to Integration, Reporting, and Market Data, ensuring alignment with business requirements and technical architecture. Stakeholder Engagement: Act as a key
Key Responsibilities Solution Design & Implementation: Lead the analysis, design, and implementation of Murex modules related to Integration, Reporting, and Market Data, ensuring alignment with business requirements and technical architecture.Stakeholder Engagement: Act as a key point
Initial Contract lenght: 6 months (possible extensions based on performance)Job type: Hybrid, Full remoteRequisites Knowledge of K8s architectureConfiguration resources: StatefulSet, Deployments, Services, Ingress, ConfigMap, Job/CronJobSecrets management (e.G. Sealed Secret Operator) and environment variablesCustomizeUse of kubectl and/or
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