Job Title: Artificial Intelligence Teaching Assistant – Summer Programs
Position Overview: TRAIN, The Coding School’s AI initiative, focuses on Machine Learning education for K-12 and beyond and is seeking Teaching Assistants for our summer Introduction to AI camps and professional development programs. Teaching assistants guide our students and/or educators through daily lab sections to support TRAIN in training the future diverse AI workforce
Location: Remote (Compatible with Eastern Time)
Compensation: Compensation is provided as a flat stipend per-program, with rates determined by the duration of instruction and the level of learners on a program-by-program basis. For this position, stipends start at $300.
Schedule: Monday-Friday during afternoon hours in Eastern Time (ET.) Specific details will be provided upon hiring. Priority will be given to candidates who can commit to several consecutive weeks more time over the summer, though there may be instances when shorter term (1-2 week) positions are available on an as needed basis.
Duties include but are not limited to:
- Prepare for and deliver synchronous, virtual instruction for introductory and intermediate artificial intelligence and machine learning lab groups of students or educators
- Facilitate virtual learning sessions via Zoom, including responsibilities such as opening the call, configuring breakout rooms, troubleshooting technical issues, and other related tasks (training will be provided)
- Participate in training sessions before the camp begins, encompassing all-faculty training, camp-specific protocols, and sexual harassment awareness.
- Attend daily faculty debrief meetings to discuss the progress and challenges faced that day during programming.
- Attend post-course debrief session (synchronous or asynchronous) to provide feedback on course
Required Qualifications include:
- Current enrollment as an undergraduate student or graduate from an undergraduate program in a relevant field such as Computer Science, Data Science, or related disciplines
- Commitment to advancing diversity, equity, and inclusion in the STEM fields
- Comfort with introductory artificial intelligence and machine learning concepts
- Must be comfortable teaching in English
Preferred Qualifications include:
- Minimum of 1 year of teaching or tutoring experience (does not need to be AI/ML-related)
- Experience in AI/ML including university courses, research, or industry experience
Additional Requirements:
- Final candidates will be subject to a background check.
About The Coding School (TCS):
TCS is a global leader in emerging tech education, ensuring that individuals are prepared with the technical skills needed for the future of work. We work with leading industry partners, such as IBM and Google, and academic institutions to develop new models of CS education to truly transform students’ lives. At the core of our mission is the belief that every student – irrespective of the industry they plan to pursue or are currently pursuing – should have foundational knowledge in emerging technologies. Furthermore, we believe we should be forward-thinking in our training, insofar as we should be training students with the skills and knowledge necessary for the future of work. Our programs have reached over 50,000 students across 125 countries in 16 specialized subjects, including Artificial Intelligence, Data Science, Quantum Computing, and more. In particular, we are committed to ensuring the future STEM workforce is diverse, equitable, and inclusive with 55% of our students from traditionally underrepresented backgrounds in STEM.
To learn more, visit the-cs.org.
Additional Information:
TCS actively strives to be a community of staff, students, and families of diverse backgrounds. TCS does not discriminate based on age, race, color, gender, gender identity, sexual orientation, religion, disability, socio-economic background, family structure, national or ethnic origin, genetic information, or military service in the administration of its policies and program.
TCS is an equal opportunity employer in both policy and practice.
Application:
To apply, complete the application here. We thank all those who apply but only shortlisted candidates will be contacted.
For questions about these opportunities or the role, please contact our team at faculty@the-cs.org.