Director, MLOps

Location: United States, Remote

Salary range: $210K–$330K annually for comparable senior-level MLOps roles.

Company

hirify.global is a specialist executive search firm focused on leaders who help organizations navigate AI transformation.

What you will do

• Own the design and evolution of the ML platform, including experiment tracking, model serving, data pipelines, and monitoring.
• Lead and mentor MLOps engineers and platform specialists while setting technical direction and best practices.
• Partner with data science and ML engineering teams to improve development workflows and accelerate production delivery.
• Drive ML deployment automation, testing frameworks, and observability strategies for reliable, reproducible, and cost-efficient systems.
• Establish governance, versioning, documentation, compliance, privacy, and data governance standards across the ML lifecycle.
• Define platform health and model performance metrics, track impact, and contribute to hiring and retention strategy.

Requirements

• 8+ years building and operating ML infrastructure, MLOps platforms, data pipelines, or related systems, including at least 3 years in a leadership or senior individual contributor role.
• Hands-on experience with model serving, experiment tracking, CI/CD for ML, containerization, Kubernetes, Airflow or equivalent orchestration, and AWS, GCP, or Azure.
• Experience shipping ML systems to production at scale across training, deployment, monitoring, and retraining.
• Strong communication skills and the ability to translate infrastructure decisions into business impact.
• Experience building, developing, and retaining high-performing engineering teams.
• Experience designing for reliability, cost efficiency, and observability in production environments.

Culture & Benefits

• Remote work arrangement in the United States.
• Opportunity consideration for future senior-level MLOps roles rather than one specific current opening.
• Potential collaboration with data science, ML engineering, security, data, and infrastructure functions.