Instructor Assistant - Machine Learning

San Francisco /
Operations /
Part time
Sphere is where vetted leading experts run live, cohort-based courses for professionals around the world.

We are building the world’s largest decentralized corporate university and growing rapidly:

- 1,300+ learners from over 700 companies globally,
- Recurring annual contracts with companies like Stripe, Flipkart, Tinder, Accenture and Flexport
- Recently part of the Y Combinator W22 batch and backed by leading investors including Felicis Ventures, Y Combinator, Uncommon Capital and leading angel investors, including the founders of Go1, Lyft, BetterUp and Flexport.

Sphere is looking for a part-time (15 - 20 hours per week) instructor assistant for their Machine Learning track. RIght now, the track offers 5 sequential courses over 5 months. This person would work closely with our Head of Content, expert instructors (people like Chip Huyen, Xavier Amatriaian, Deepak Agarwal, Hugging Face, Jeff Heer, and Ronny Kohavi) and professional learners to help refine the course content and improve overall learner experience.

What you’ll do at Sphere:

- Research what is trending in the course topic area to inform course content development
- Help develop the course content by reviewing course descriptions, session overviews, session outlines, and presentation slides
- Provide valuable feedback on related marketing materials such as our Machine Learning blog content and social media posts
- Attend the live courses in the Sphere portal and help build the learner community by managing their questions, sharing links to relevant content, and driving conversation/debate

We think the person who will be most successful in this role is described below (but we're open to being proven wrong!):

- They are earning, have a degree in, and/or have worked in a computer science or data science field 
- They are actively engaged in online or offline data communities
- They have teaching or tutoring experience (e.g., as a TA) in computer science or data science
- They have published content about data science before (articles, white papers, blog posts, podcasts, social media posts, etc.)
- They have experience managing communities online
- They are self-directed, creative and curious
- They can tackle problems and challenges with minimal direction
- They can consistently execute on goals

Why you’ll love working at Sphere:

- Your professional network will explode: You will work one-on-one with true pioneers in machine learning who can open doors for you in your career. And you will become a part of multiple learner communities with people from leading companies already doing the work you may wish to do in the future.
- You will be working in a fast-paced, startup backed by some of Silicon Valley's leading investors.
- We’re a kind, hard-working and passionate team that embraces remote work.

Sphere is an Equal Opportunity Employer.

Note: This role requires someone in a US-friendly time zone