MLOps Architect

VirtualVocations; Nashville (TN); Remote; USD 120,000 - 160,000; Full time

Job summary

A leading remote job platform in Nashville is seeking an experienced MLOps Platform Architect to lead the design and implementation of machine learning platforms. The role involves architecting end-to-end MLOps solutions, ensuring scalability and reliability, while managing client expectations. Ideal candidates should have over 13 years of experience in data engineering and machine learning, with strong expertise in Databricks and cloud platforms.

Qualifications

• 13+ years of professional experience in data engineering, machine learning, or software architecture.
• Experience in building and deploying production-grade MLOps platforms.
• Expertise with the Databricks ecosystem for scalable data and ML workflows.
• Experience with at least one major cloud platform and its MLOps-related services.
• Understanding of the machine learning lifecycle from data ingestion to model serving.

Responsibilities

• Architect and build end-to-end MLOps platforms ensuring scalability, reliability, and security.
• Act as a primary technical point of contact for clients, managing expectations and project requirements.
• Drive the technical vision for the MLOps practice, establishing best practices for model development and deployment.

Skills

Data engineering

Machine learning

Software architecture

MLOps

Databricks ecosystem

AWS

GCP

Azure

Job description

A company is looking for an MLOps Platform Architect to lead the design and implementation of machine learning platforms.

Key Responsibilities

Architect and build end-to-end MLOps platforms ensuring scalability, reliability, and security

Act as a primary technical point of contact for clients, managing expectations and navigating project requirements

Drive the technical vision for the MLOps practice, establishing best practices for model development and deployment

Required Qualifications

13+ years of professional experience in data engineering, machine learning, or software architecture with a focus on MLOps

Proven experience in building and deploying production-grade MLOps platforms

Strong expertise with the Databricks ecosystem for scalable data and ML workflows

Extensive experience with at least one major cloud platform (AWS, GCP, or Azure) and its MLOps-related services

Deep understanding of the entire machine learning lifecycle, from data ingestion to model serving and monitoring