Lead Instructor: MLOps / AI Platform Engineering

Job Title Lead Instructor: MLOps / AI Platform Engineering Client: Confidential – Customer Success Reskilling Location: Remote ( Must work West Coast / Pacific Time hours ) Duration: 2 Weeks (Starting Mid-June) Commitment: Roughly 30 hours per week Compensation: $11,500 - $15,500 (Estimated lump sum payment for one 60-hour program) About the Engagement General Assembly is delivering a specialized reskilling program designed to transition Customer Success and Account Management professionals into MLOps and AI Platform Engineering roles. Role overview: As the Lead Instructor, you will be the face of lessons. You will lead experienced customer-facing professionals through the complexities of taking AI systems from pilot to production, ensuring they leave the 2-week intensive with a functional understanding of MLOps governance and deployment. What You’ll Do Lead Live Instruction: Deliver high-energy, synchronous remote lectures and "prompt-along" sessions covering ML pipelines, model deployment, and monitoring. Simplify the Complex: Translate high-level MLOps concepts (CI/CD for ML, governance frameworks) into digestible insights for learners who are experienced professionals but not career engineers. Facilitate Hands-on Labs: Guide students through self-paced exercises and live troubleshooting within the Azure AI Foundry and ML environments. Mentor & Office Hours: Provide real-time feedback during dedicated lab hours, helping students navigate technical roadblocks in Python and Azure infrastructure. Drive Learning Outcomes: Ensure students can successfully articulate and execute model lifecycle management strategies by the end of the cohort. What You Bring The Experience: 7+ years in software or data engineering, with at least 3+ years specifically in MLOps or ML platform roles in a production environment. The "Teacher" Gene: Proven experience in technical instruction, bootcamp delivery, or corporate training. Ability to read the room in a virtual setting. Azure Fluency: Deep, hands-on expertise with Azure ML and AI Foundry. Ability to navigate these platforms proficiently. Technical Foundation: Proficiency in Python, Data Engineering fundamentals, and applying DevOps/CI/CD principles specifically to ML workloads. The Credentials: AZ-900, AI-900, and DP-100 are required; AI-102 is preferred. The Pedigree: Experience as an AI Platform or Azure ML engineer at a major tech firm (e.g., Microsoft, Google) is a plus. Note on Schedule This is a high-intensity, 2-week engagement. Candidates must be fully available for 30 hours per week during the mid-June window and operate on Pacific Time (PT) schedules to align with the learner cohort. Location and Eligibility Remote positions may be performed from approved General Assembly operating countries: United States, Canada, United Kingdom, Australia, and Singapore. #J-18808-Ljbffr