We are looking for an experienced Subject Matter Expert (SME) with deep expertise in MLOps, scalable ML engineering, cloud infrastructure, and secure deployment of AI systems. This role will focus on supporting the development and review of advanced course content designed to upskill professionals in building, shipping, and securing production-grade ML applications.
You’ll guide learners through the full engineering lifecycle — from writing testable ML code, to containerization, orchestration, release management, and enforcing security best practices in real-world deployments.

QUALIFICATIONS:

• 5+ years of hands-on experience in ML engineering, DevOps, or MLOps roles.
• Strong proficiency in Python with experience applying TDD principles in ML workflows.
• Deep working knowledge of Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure).
• Experience designing and deploying secure APIs and scalable ML inference systems.
• Familiarity with GPU resource management and container-based model serving.
• Understanding of cloud security standards, guardrails, and infrastructure monitoring.

• Analyze/create learning objectives for each course.
• Review/create Course Outline for each of the courses.
• Review video scripts (7-9 per course) and confirm technical accuracy of the content, suggest edits and updates as required. Incorporate one round of internal and client feedback.
• Provide relevant static or recorded demos/ screencast to be integrated in the videos. Incorporate one round of internal and client feedback.
• In case of AI/software/tool-based courses, suggest relevant freeware. Write/review and test the codes to check.
• Review readings (4-6 per course, each up to 1200 words) and confirm technical accuracy of the content, suggest edits and updates as required. Incorporate one round of internal and client feedback.
• Create hands-on activities (1-2 lab or any other client preferred format) per course. Incorporate one round of internal and client feedback.
• Review practice quiz and graded assessments (5 files, each comprising 5-10 questions) and suggest suitable edits, confirm technical accuracy. Incorporate one round of internal and client feedback.
• Record talking head videos (onsite/virtually on Zoom) for each course. There will be approx 20-25 minutes of video recording involved per course. Incorporate one round of internal and client feedback.
• Provide digital signatures to be included on the client platform.
• For all reviews - validate the content accuracy and provide recommendations/suggestions, write/re-write to fill content gaps as necessary, write/test codes and labs, incorporate 1 round of internal feedback and 2 rounds of client feedback.
• Be available for Client discussions and content discussions as and when required.