Who we are
Fizz is a private and authenticated platform designed to revolutionize the social fabric of communities, starting with colleges. After verifying a university email address, students use Fizz to post questions, memes, polls, and chat directly with other verified students, all while maintaining full control of their identity and privacy. Fizz communities are safe, authentic, and inclusive, made possible through community-based moderation.
Launched by two Stanford dropouts, Fizz is currently expanding into colleges all across the US. In a time when social media is plagued by curated highlight reels and lack of authenticity, Fizz is on a mission to redefine the definition of a true social network.
What we’ve done
We first launched Fizz at Stanford in July 2021 and have since seen >95% of undergraduates join the app, half of which use Fizz every day. Since then, we have raised over 16M from NEA, Owl Ventures, and Lightspeed, built a rock-solid engineering team with decades of experience at top tech companies, and expanded Fizz to be the dominant community platform at 70+ colleges.
Where we’re going
Our near term goal is to expand to all US universities by the end of the 2023-2024 academic school year. To get there, we give engineers at Fizz a lot of autonomy and ownership of our product. Some of the things you can expect to work on include:
- Building and maintaining scalable human in the loop AI community moderation systems
- Utilizing NLP systems to automatically categorize and target content to users
- Conducting analysis on larger amounts of user-generated content and using data to drive product decisions
We are open to candidates of all experience levels who are passionate about being an early employee and want to help drive our company forward.
Responsibilities
- Design and implement machine learning models and algorithms to solve specific user problems
- Develop in-house human in the loop moderation systems to detect and prevent inappropriate content and behavior on our platform
- Develop and maintain data pipelines and infrastructure to support machine learning workflows
- Work closely with the front-end team to implement content moderation and content recommendation systems
- Keep up-to-date with emerging trends and best practices in machine learning and AI development
Qualifications
- Strong understanding of machine learning techniques and algorithms (natural language processing, generative AI, content recommendation)
- Experience as a lead engineer for at least one large scale system that supports at least a million users using a distributed system.
- Familiarity with designing RESTful APIs that are scalable, reliable, and secure
- Strong grasp on product and ability to develop a product that college students will use and love.
- Passion for building intelligent systems that can improve the user experience and safety of our platform
Bonus Points
- Experience working with User-Generated Content or a Trust & Safety team.
- Experience with TypeScript, Firebase, or Google Cloud Platform.
Fizz is committed to a policy of Equal Employment Opportunity and will not discriminate against an applicant, candidate, or employee on the basis of race, color, religion, creed, national origin or ancestry, sex, gender, gender identity, gender expression, sexual orientation, age, physical or mental disability, medical condition, marital/domestic partner status, military or veteran status, genetic information or any other legally-recognized protected basis under federal, state or local laws, regulations or ordinances.
