Artificial Intelligence Consultant

Virtusa

Madrid, Spain

4 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.buscojobs.com.es

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Continuous Integration Information Engineering Python (Programming Language) Machine Learning Performance Tuning Tensorflow Pytorch Large Language Models IT Architecture

+5 more

HybridCloud AI Platforms Kubernetes Machine Learning Operations Databricks

Job description

Enterprise Architecture experience: proven EA leadership translating concepts into- Hands-on AI/ML engineering: building, fine-tuning, and deploying ML/DL models (LLMs, RAG, MLOps) in production.- AI platforms: hands-on with AWS (Bedrock, SageMaker, Amazon Q), Azure (Azure AI, ML, OpenAI), and Databricks.- Engineering and analytics: strong Python, TensorFlow/PyTorch, containers, Kubernetes, and CI/CD for hybrid cloud.- Data modelling and governance: conceptual/logical modelling and governance standards in regulated environments.- Architecture judgement: select fit-for-purpose AI architecture per use case, with full-lifecycle- Leadership: lead a small team of AI architects and help shape enterprise AI strategy and direction.- Degree in data science, AI engineering, or a related field (or equivalent experience).- Postgraduate degree in MIS, AI, data science, or a related field.- Recognised thought leader in applying AI within the enterprise and across the industry.- Extensive senior AI, data science, data engineering, and AI architecture experience delivering- Hands-on building AI models, including LLMs and LVMs, across diverse data types#J-*****-Ljbffr

Requirements

Enterprise Architecture experience: proven EA leadership translating concepts into- Hands-on AI/ML engineering: building, fine-tuning, and deploying ML/DL models (LLMs, RAG, MLOps) in production.

AI platforms: hands-on with AWS (Bedrock, SageMaker, Amazon Q), Azure (Azure AI, ML, OpenAI), and Databricks.
Engineering and analytics: strong Python, TensorFlow/PyTorch, containers, Kubernetes, and CI/CD for hybrid cloud.
Data modelling and governance: conceptual/logical modelling and governance standards in regulated environments.
Architecture judgement: select fit-for-purpose AI architecture per use case, with full-lifecycle- Leadership: lead a small team of AI architects and help shape enterprise AI strategy and direction.
Degree in data science, AI engineering, or a related field (or equivalent experience).
Postgraduate degree in MIS, AI, data science, or a related field.
Recognised thought leader in applying AI within the enterprise and across the industry.
Extensive senior AI, data science, data engineering, and AI architecture experience delivering- Hands-on building AI models, including LLMs and LVMs, across diverse data types#J-*****-Ljbffr