Overview
Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - 12 Month(s)
Skills
Docker
Conflict Resolution
Continuous Delivery
Continuous Integration
Data Science
Computer Science
Artificial Intelligence
Cloud Computing
Generative Artificial Intelligence (AI)
Machine Learning (ML)
DevOps
Electronic Engineering
Management
Microsoft Azure
Problem Solving
Machine Learning Operations (ML Ops)
Communication
IaaS
Kubernetes
Linux
Prototyping
Python
SQL
GC
Scalability
Collaboration
Training
Job Details
Job Title: AI/ML Architect
Location: Northbrook, IL 100% Onsite
Duration: 6 Months
Only: & Citizen
Interview: Immediate
Must-Have Skills (Weightage):
- Microsoft Azure ML Architecting Experience 40%
- Microsoft Azure AI Architecting Experience 40%
- Microsoft Azure DevOps Architecting Experience 20%
Role Overview
As an AI/ML Architect on the Data Science team, you will be responsible for designing and operationalizing enterprise-grade machine learning solutions in the cloud. You will collaborate with data scientists, engineers, and architects to ensure scalable, reliable, and cost-effective deployments while adhering to best practices in MLOps.
Key Responsibilities
- Design and implement scalable, cloud-native ML pipelines for production AI solutions.
- Collaborate with Data Scientists to transform prototypes into production-ready solutions.
- Deploy and manage ML models using Azure Machine Learning and AKS.
- Containerize and orchestrate services using Docker and Kubernetes.
- Optimize cloud infrastructure for performance, scalability, and cost efficiency.
- Implement robust monitoring, logging, and CI/CD practices to support AI operations (MLOps).
- Work with enterprise cloud architects to align AI/ML solutions with infrastructure standards.
- Contribute to best practices for AI/ML systems in production environments.
Qualifications
- 12+ years of IT/Data Science experience, with 3+ years in ML engineering within cloud environments.
- Proven expertise in Azure Machine Learning, Docker, and AKS.
- Strong background in building cloud-native ML pipelines for training, deployment, and monitoring.
- Familiarity with Generative AI concepts (operationalization experience is a plus).
- Proficiency in Python, SQL, and Linux-based environments.
- Strong understanding of MLOps, CI/CD pipelines, and production APIs.
- Excellent communication and problem-solving skills with ability to work cross-functionally.
Education
- Bachelor s degree in Computer Science, Data Science, Electronic Engineering, or related field.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.