MLOPS Architect

TechDigital Group; Jersey City (NJ); On-site; USD 120,000 - 150,000; Full time

Job summary

A technology solutions firm located in Jersey City is seeking an experienced MLOps Architect to design and implement end-to-end pipelines using Azure. The ideal candidate will have strong experience in cloud technologies, container orchestration, and ML governance. Responsibilities include documenting workflows, providing technical oversight, and collaborating with data scientists and engineers. This role offers an exciting opportunity in a fast-paced environment.

Qualifications

• Experience with Azure Machine Learning and Azure OpenAI is required.
• Proficiency in Python, Docker, and Kubernetes is essential.
• Familiarity with MLflow and Terraform is a plus.

Responsibilities

• Document architecture and workflows for compliance.
• Architect end-to-end MLOps pipelines using Azure.
• Collaborate with data scientists on model deployment.

Skills

Azure Machine Learning

Python

Docker

Kubernetes

CI/CD pipelines

LLM fine-tuning

Prompt engineering

Model deployment

Tools

Azure OpenAI

Azure DevOps

MLflow

Terraform

Prometheus

Grafana

Job description

Responsibilities

• Document architecture, workflows, and best practices for knowledge sharing and compliance.
• Provide technical oversight & Guidelines
• Architect and implement end-to-end MLOps and LLMOps pipelines using Azure Machine Learning and Azure OpenAI.
• Design scalable infrastructure for training, deploying, and monitoring ML and LLM models in production.
• Collaborate with data scientists and engineers to streamline model development, testing, and deployment workflows.
• Manage Azure Kubernetes Service (AKS) clusters and containerized ML workloads.
• Ensure model governance, versioning, and reproducibility using tools like MLflow and Azure DevOps.
• Promote DevSecOps practices, ensuring security and compliance are embedded in the ML lifecycle.
• Monitor and troubleshoot production ML systems, ensuring high availability and performance.

Qualifications

• Experience with Azure Machine Learning, Azure OpenAI, Azure DevOps, and AKS.
• Proficiency in Python, Docker, Kubernetes, and CI/CD pipelines.
• Experience with LLM fine-tuning, prompt engineering, and model deployment.
• Familiarity with MLflow, Terraform, and monitoring tools like Prometheus/Grafana.