Über diese Lead Instructor: MLOps / AI Platform Engineering Stelle bei General Assembly
Since 2011, General Assembly has transformed tens of thousands of careers through pioneering, experiential education in today’s most in-demand skills. As featured in The Economist, Wired, and The New York Times, GA offers training in web development, data, design, business, and more, both online and at campuses around the world. Our global professional community boasts 60,000 full- and part-time alumni — and counting. In addition to fostering career growth for individuals, GA helps employers cultivate top tech talent and spur innovation by transforming their teams through strategic learning. More than 21,000 employees at elite companies worldwide have honed their digital fluency with our upskilling and reskilling initiatives. GA has also been recognized as one of Deloitte’s Technology Fast 500, and Fast Company has dubbed us leaders in World-Changing Ideas as well as the #1 Most Innovative Company in Education.
GA is at the leading edge of creating practical solutions to one of the most pressing challenges of our time - the future of work. As recognized by The World Economic Forum, BCG, the OECD and more, these are big challenges to which only a few companies are offering real solutions. In this role, you'll be speaking every day to corporate leaders who rely on GA to help them apply these solutions to their workforce of the future.
Job Title: Lead Instructor: MLOps / AI Platform Engineering
Company: General Assembly
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.
As the Lead Instructor, you will be the face of lessons. You aren't just checking the math; you are bridge-building. 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. You should be comfortable "reading the room" in a virtual setting.
- Azure Fluency: Deep, hands-on expertise with Azure ML and AI Foundry. You should be able to navigate these platforms in your sleep.
- 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 (Microsoft, Google, etc.) is a massive 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 be prepared to operate on Pacific Time (PT) schedules to align with the learner cohort.
Unless 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.
