MLOps / AI Platform Engineer Subject Matter Expert
Jobgether
full-remoteseniorfixed-termbackendproduct-management United States Yesterday via LinkedIn
72,000 - 90,000 USD/annual
See how well this job matches your profile
Sign up to get an AI match score and generate a tailored application in seconds.
Get your match scoreTags
MLOpsMachine Learning PipelinesModel DeploymentModel MonitoringML GovernanceCI/CDDevOpsPythonAzure MLAzure
About the role
Role overview
The engagement is a short-term, high-impact SME role validating and refining an advanced reskilling pathway for MLOps and AI platform engineering. You will act as the primary technical authority, ensuring the curriculum is technically accurate, realistic, and appropriately leveled for experienced professionals transitioning into the field.
Responsibilities
- Review and validate competencies, learning objectives, and the technical curriculum for an MLOps / AI Platform Engineering pathway.
- Assess instructional materials covering:
- ML pipelines
- Model deployment
- Monitoring
- Governance to ensure technical correctness and industry alignment.
- Evaluate asynchronous learning assets (exercises and guided activities) for accuracy, complexity, and suitability.
- Participate in a structured SME review cycle and deliver consolidated, actionable feedback for instructional designers.
- Ensure content reflects real production ML practices, including scalability, reliability, and operational governance.
Requirements
- 7+ years of experience in software or data engineering.
- 3+ years in MLOps or ML platform engineering roles in production environments.
- Strong hands-on expertise with ML pipelines, model deployment, monitoring, and governance at scale.
- Solid understanding of DevOps principles and CI/CD workflows applied to ML systems.
- Proficiency in Python and data engineering fundamentals.
- Cloud experience, preferably Azure.
- Experience with Azure ML and AI platform engineering patterns; exposure to full model lifecycle management.
- Familiarity with relevant certifications (e.g., AZ-900, AI-900, DP-100; AI-102 preferred).
- Strong communication skills to translate complex feedback for non-engineering audiences.
Nice to have
- Experience in leading AI platform environments (Microsoft, Google, or similar).
Engagement details
- Fully remote and flexible, asynchronous work with a focused review cycle.
- Part-time: 15–20 hours per week.
- Short-term project: 6–7 weeks.
- Competitive hourly compensation: $60–$75/hour.
Scraped 4/24/2026