Azure AI/ML Architect

Overview

Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

Azure
Artificial Intelligence
AI/ML
Data Science
DevOps
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Generative Artificial Intelligence (AI)
Microsoft Azure
Docker
Python
SQL

Job Details

Role: Azure AI/ML Architect

Location: Hybrid role (3 days onsite) Northbrook, IL

Type; Contract

Job Description

This is a Hybrid role (3 days onsite) Northbrook, IL

Must-Have Skills:

Microsoft Azure ML Architecting Experience 40% weightage

Microsoft Azure AI Architecting Experience 40% weightage

Microsoft Azure DevOps Architecting Experience 20% weightage


As an AI Architect on the Data Science team, you will play a key role in productionizing machine learning models, building robust pipelines, and enhancing the overall AI platform. This role requires hands-on experience with Azure, Docker, and Azure Kubernetes Service (AKS), as well as strong knowledge of cloud-native MLOps best practices.


Responsibilities

  • Design and implement scalable, cloud-native ML pipelines for production AI solutions.
  • Collaborate with data scientists to operationalize ML models from prototypes to production.
  • Manage deployment of ML models using Azure Machine Learning and AKS.
  • Develop, containerize, and orchestrate services using Docker and Kubernetes.
  • Optimize cloud data and compute architectures to ensure cost-effective and reliable deployments.
  • Implement robust monitoring, logging, and CI/CD practices to support AI operations (MLOps).
  • Work closely with enterprise cloud architects to align AI solutions with client s infrastructure standards.
  • Contribute to the evolution of the best practices around AI/ML systems in production environments.

Qualifications

  • Minimum 12 years of experience as a Data Scientist, with at least 3 years focused on machine learning engineering in cloud environments.
  • Proven experience deploying ML models in Azure, preferably with Azure Machine Learning, Docker, and AKS.
  • Hands-on experience building cloud-native pipelines for model training, scoring, and monitoring.
  • Familiarity with GenAI concepts and tools (experience operationalizing GenAI is a plus).
  • Proficiency in Python, SQL, and Linux-based development environments.
  • Strong understanding of MLOps principles, CI/CD pipelines, and production-grade APIs.
  • Effective communicator with strong problem-solving skills and ability to work across teams.

Education

  • Bachelor s degree in Computer Science, Electronic Engineering, Data Science, or a related field.
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