MLOps / AI Platform Engineer Subject Matter Expert at General Assembly | Torre
MLOps / AI Platform Engineer Subject Matter Expert
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General Assembly

MLOps / AI Platform Engineer Subject Matter Expert

General Assembly
Emma
Emma
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Freelance
Recurrent (~20 hours per week)
Compensation
USD60 - 75/hour
location_on
Remote (for United States residents)
Remote (for Canada residents)
Remote (for United Kingdom residents)
Remote (for Australia residents)
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Emma of Torre.ai
 1 day ago

Requirements and responsibilities

Company: General AssemblyClient: Confidential -  Customer Success ReskillingStart: ASAPHours: 15 to 20 hours a week, for 6 to 7 weeks (for a grand total of 90 to 140 hours) (Ends by July, 2026) (Most of your hours will be asynchronous - you will be vetting and iterating with our team - not building content from scratch yourselves.)Compensation Range:  $60 - $75 per hourLocation: RemoteAbout the engagementGeneral Assembly is building a reskilling program for clients' Customer Success and Account Management professionals transitioning into MLOps and AI Platform Engineering roles. You'll serve as the subject matter expert for Pathway 3, validating the technical accuracy of pipeline content, governance frameworks, monitoring exercises, and async assets designed to bring CSAMs up to speed on taking AI systems from pilot to production at scale.What you'll doReview and validate competencies and learning objectives for the MLOps / AI Platform Engineer pathwayValidate technical accuracy of instructional slide content covering ML pipelines, model deployment, monitoring, and governanceReview async assets including prompt-alongs and self-paced exercises for technical correctness and appropriate difficulty level for the learner population (experienced customer-facing professionals, not engineers)Participate in one structured SME review gate (approximately 1 week, early June)Provide a single round of revision feedback for the LED to implement before QAWhat you bring7+ years in software or data engineering with 3+ years in MLOps or ML platform roles in productionHands-on experience with ML pipelines, model deployment, monitoring, and governance at scaleStrong DevOps and CI/CD fundamentals applied to ML workloadsPython proficiency, data engineering foundations, and Azure cloud infrastructure fluencyFamiliarity with Azure ML, AI Foundry platform engineering patterns, and model lifecycle managementAZ-900, AI-900, and DP-100 minimum; AI-102 preferredFormer AI Platform or Azure ML engineer with Microsoft, Google, or similar company is a strong plusUnless otherwise noted, remote positions can be performed from the following approved General Assembly operating countries.United States of America (states of operation may vary), Canada (provinces of operation may vary), United Kingdom, Australia, and Singapore.
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