Curriculum Developer - School of Computer Science - LTI at Carnegie Mellon University in Pittsburgh, PA

Job description

Carnegie Mellon University is a private, global research university that stands among the world’s most renowned education institutions. With ground-breaking brain science, path-breaking performances, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the curious to deliver work that matters, your journey starts here! The Language Technologies Institute (LTI) at Carnegie Mellon University is a world-renowned research and education hub at the forefront of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding, processing, and generating human language in both written and spoken forms. The Curriculum Developer serves as the academic implementation lead and pedagogical architect for the certificate, ensuring that the individual courses form a coherent, integrated, and high-quality educational experience. Working closely with the Faculty Certificate Director, Faculty Course Directors, Adjunct Preceptors, CMU Online, and the Certificate Operations Manager, this role provides continuity as instructors, technologies, and course offerings evolve. The Curriculum Developer is responsible for curriculum integration, instructional quality, online pedagogy, and continuous improvement. Core Responsibilities Curriculum Integration: Ensure coherence across courses; Align learning objectives, prerequisites, and assessment philosophy; Eliminate unnecessary overlap while identifying curricular gaps; Maintain curriculum roadmap. Course Development : Develop detailed course structures; Design assignments and projects; Develop laboratories and instructional materials; Coordinate assessment design; Support online pedagogy appropriate for professional learners. Annual Curriculum Refresh: Coordinate annual updates by reviewing advances in the field, incorporating new tools and models, updating laboratories, refreshing case studies, replacing obsolete technologies, recommending curriculum improvements to Faculty Course Directors. CMU Online Coordination: Serve as the primary liaison with CMU Online by coordinating: video production, recording schedules, instructional design, accessibility, multimedia development, Learning Management System organization and publishing. Preceptor Support: Provide instructional continuity by onboarding new Adjunct Preceptors, preparing instructor guides, coordinating teaching materials, ensuring consistency across offerings, supporting integration of industry case studies. Quality Assurance: Prior to each offering, review instructional materials, validate laboratories and software environments, verify assignments and grading rubrics, ensure all instructional assets function correctly, coordinate revisions based on student feedback. Continuous Improvement: Analyze course evaluations, review learning analytics, identify opportunities for improvement, recommend instructional innovations, coordinate certificate-wide enhancements. Cross-Certificate Coordination: Collaborate with other Certificate Curriculum Developers to identify opportunities for shared courses, harmonize prerequisites, maximize reuse of instructional assets, maintain consistency across the LTI certificate ecosystem. Adaptability, excellence, and passion are vital qualities within Carnegie Mellon University. We are in search of a team member who can effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work. Qualifications: Bachelor's Degree in Computer Science or a related field. 3 to 5 years of operating systems administrative experience including experience with Python, Large Language Models (LL