United States onlySince 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.
Company: General Assembly
Client: Confidential - Customer Success Reskilling
Start: ASAP
Hours: Part time & Flexible - up to 35 hours per week (Ends by July, 2026)
Compensation Range: $60 - $80 per hour
Location: Remote
About the engagement
General 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 do
- Review and validate competencies and learning objectives for the MLOps / AI Platform Engineer pathway
- Validate technical accuracy of instructional slide content covering ML pipelines, model deployment, monitoring, and governance
- Review 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 QA
What you bring
- 7+ years in software or data engineering with 3+ years in MLOps or ML platform roles in production
- Hands-on experience with ML pipelines, model deployment, monitoring, and governance at scale
- Strong DevOps and CI/CD fundamentals applied to ML workloads
- Python proficiency, data engineering foundations, and Azure cloud infrastructure fluency
- Familiarity with Azure ML, AI Foundry platform engineering patterns, and model lifecycle management
- AZ-900, AI-900, and DP-100 minimum; AI-102 preferred
- Former AI Platform or Azure ML engineer with Microsoft, Google, or similar company is a strong plus
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.
Australia
United Kingdom
Singapore
Canada
Saudi Arabia