Learning Engineer - School of Computer Science - CS

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 Technology for Effective and Efficient Learning (TEEL) Lab at CMU is seeking a Learning Engineer to contribute to educational and research projects in emerging technology areas. At the TEEL Lab, we collect and analyze student data to inform the development and maintenance of technology-enhanced learning tools and design of features that enable learning research. New initiatives include the development of infrastructure and content for large-scale workforce training programs in cloud computing, data science, and AI/ML. Training delivery is administered through partnerships with higher education organizations as well as industry partners. Research experiments are typically conducted as part of the training delivery to evaluate the efficacy of our methods. Special emphasis will be put on training individuals in the adoption, use, and operation of AI/ML systems. The earning Engineer will be a member of our team developing, maintaining, and utilizing a project-based online social learning platform for workforce training at scale.

The Learning Engineer is expected to develop interactive learning materials in one or more of the target areas. This process includes designing content that maps to a set of learning objectives, the development of a proof of concept, and deploying a production-ready project module on our cloud-hosted infrastructure. This position also involves developing appropriate metrics for assessing student learning, collecting, analyzing, and interpreting data on student learning, attitudes, and engagement, reporting on assessment data and research-based pedagogical strategies, disseminating best practices, research, and emerging developments on formative assessment, including partnering with faculty to publish assessment work. The position may also include consulting with instructors about teaching and course design, especially as it relates to effective assessment practices. Finally, the position will entail leading learning engineering research activities, such as academic writing, quantitative data collection and visualization, and design and conduct of qualitative research (e.g. interviews or surveys).

Flexibility, excellence, and passion are vital qualities within Carnegie Mellon University. Inclusion, collaboration and cultural sensitivity are valued competencies at CMU. Therefore, we are in search of a team member who is able to 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 or higher in Computer Science, Instructional Design, Learning Sciences, or a related field.
• Demonstrated experience of applying rigorous quantitative and/or qualitative research methods to empirically study a research question.
• Experience in applied ML, natural language processing (NLP), or data science.
• Experience securely managing and analyzing complex data sets.
• Strong oral and written communication skills, including maintaining confidentiality.
• Ability to work collaboratively, effectively, and professionally in settings of social and intellectual diversity.
• Ability to successfully navigate ambiguity, balance multiple competing responsibilities, meet deadlines on time, and meticulously pay attention to detail.
• Sensitivity to teaching and learning needs at a research university.

Preferred Qualifications:

• Experience with commercial cloud services such as Microsoft Azure, AWS or Google Cloud Platform.
• Experience with web service development frameworks.
• Full-stack development with HTML, CSS, Javascript, Python.
• Experience with RESTful web services.
• Experience with SQL and NoSQL databases.
• Experience building, deploying, monitoring and troubleshooting containerized microservices using Docker, Kubernetes and Helm.

Requirements:

• Successful background check

Are you interested in this exciting opportunity?! Apply today!

CMU’s COVID-19 Vaccination Requirements: As a condition of employment, Carnegie Mellon University requires all staff and faculty working in the United States to be fully vaccinated, including a booster when eligible, against COVID-19. Prior to commencement of employment, new hires in the United States must provide proof of vaccination or obtain an approved exemption. (Exemptions may be requested for medical reasons or for religious or strong moral or ethical conviction.) Staff and faculty must comply with all applicable COVID-19 mitigation requirements. Please see Minimum Requirements to Return to Campus for details regarding the university’s current COVID-19 mitigation requirements.

Location

Pittsburgh, PA

Job Function

Eberly Center

Position Type

Staff – Fixed Term (Fixed Term)

Full Time/Part time

Part time

Pay Basis

Hourly

More Information:

• Please visit “ Why Carnegie Mellon ” to learn more about becoming part of an institution inspiring innovations that change the world.
  
  
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• Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran .
  
  
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