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AI Engineer - Azure AI Foundry Specialist at NTT DATA

Plano, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Mar, 26

Salary

0.0

Posted On

13 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure AI Foundry, Azure OpenAI, Azure ML Studio, Azure Kubernetes Service, Terraform, YAML Pipelines, DevOps, TensorFlow, PyTorch, Keras, spaCy, Scikit-learn, Python, Django, Flask, FastAPI

Industry

IT Services and IT Consulting

Description

Build applications in prediction, recommendation, text analytics, computer vision, bots, and document intelligence. Enhance GenAI solutions using RAG models and Agents Frameworks for intelligent information retrieval. Employ deep technical knowledge of Azure AI Foundry, Azure OpenAI, Azure ML Studio, and Azure Kubernetes Service (AKS). Deploy cloud services using Terraform templates, YAML pipelines, and DevOps best practices. Apply advanced knowledge of ML frameworks: TensorFlow, PyTorch, Keras, spaCy, scikit-learn. Work with LLM frameworks, APIs, embedding models, and vector databases (e.g., Hugging Face). Fine-tune, quantize, and deploy models across cloud environments. Develop scalable applications using Python frameworks (Django, Flask, FastAPI, Django Rest). Design modular integrations between cloud-based services via APIs. Create and maintain infrastructure to ingest, normalize, and combine datasets for actionable insights. Handle large-scale data streams in distributed computing environments. Communicate complex technical concepts clearly to non-technical audiences. Collaborate with clients and stakeholders to ensure satisfaction and project success. 8+ years of experience with Azure AI Foundry, Terraform, Azure Kubernetes Service (AKS) 5+ years hands on experience with AI/ML projects (Predictive Analytics, Generative AI, ML Ops). 3+ years of hands-on Python development. Ability to travel up to 50% as required.

Responsibilities

The AI Engineer will build applications in various AI domains such as prediction, recommendation, and computer vision. They will enhance GenAI solutions and deploy cloud services while ensuring effective communication with clients and stakeholders.