Love language? So do we, and our mission is to infuse AI with that same love.
At Surge, we're building the human infrastructure to power NLP — from detecting hate speech, to parsing complex military documents, to injecting human values into the next wave of language models. Our first product is a platform that helps ML teams create amazing, human-powered datasets to train AI in the richness of language.
We're a well-funded team of engineers, scientists, and linguists from Google, Facebook, Twitter, Airbnb, Harvard, and MIT. We're rapidly growing, and we partner with top companies and research labs around the world.
To apply, please email [email protected] with a resume and 2-3 sentences describing your interest in Surge. We love personal projects and writings too!
What we’re looking for
- You love engaging with customers and making sure they’re having a great experience. You’ll work with them to understand their SLAs and goals, and run data delivery projects to meet them.
- You’re a great communicator. You can explain technical concepts in simple terms.
- You have experience with spreadsheets and data manipulation. You know how to analyze data and parse it into various forms.
- You love productivity tools. Missed deadlines irk you, and you’re always looking for ways to make things more efficient.
- You’re excited about joining a small team. You’ll be the first full-time member of the customer success team and will have the opportunity to grow into a leadership position.
- You love language and writing. Thinking about the nuances of language and explaining it to others fascinates you.
- Bonus: You’re familiar with AI and data labeling.
- Engage with customers building language models and maximize the value they get from our platform.
- Run projects and interact with data labelers to ensure they perform a great job.
- Mock up customer pain points into new product ideas for our engineering team, spec out new features, and shape the product roadmap to best serve our current and future customers.
Some examples of the problems we are solving
- Language is difficult. Imagine categorizing documents based on complex financial terminology that even the average financial analyst isn’t familiar with. How do you work with customers to understand their accuracy vs. speed tradeoffs, and how do you find and train labelers to do a good job?
- We operate in 20+ languages. When different cultures have different concepts of hate speech, how do you translate and communicate this effectively?