- San Francisco
- Ruby on Rails
We're looking for a fullstack engineer to join as the third member of our engineering team. The role will be a mix of backend (rails, python, golang) and frontend (react), with exposure to devops and machine learning as desired. We prefer candidates with a desire to take end-to-end ownership over projects (i.e. help shape the product direction, work with designers to make UI/UX decisions, and review/distill usage metrics).
VoiceOps is creating the voice AI of the future. We're working towards being able to intricately structure and understand human dialog. Parsing sales conversations, and helping sales leaders use the data to coach, train, and evaluate their team's success is our first step on this huge journey.
VoiceOps uses AI to improve call center rep performance with world-class coaching.
Our average customer makes tens of thousands of calls per week. In a world without VoiceOps, they have literally no idea what their sales reps are doing on the phone. It's a total (and scary) black box.
By applying ML and a great UI to this problem, call center leadership has all the data they need about customer conversations at their fingertips, and can coach their reps more effectively and efficiently.
The technical problem is interesting, and gets more interesting as we grow. Our core challenge is how to take billions of audio recordings (and messy, unstructured human conversations) and make sense out of that data in a way that is: a) accurate b) cost efficient, and c) highly scalable. The corresponding product problem is how to take well-structured data and make it actionable for the end-user.
Call center recordings are one of the richest/largest untapped datasets in the world (literally, billions of calls stored in AWS buckets that no one is touching right now). We're going to be the best in the world at structuring that data and putting it to use to make businesses work better.
Every problem is our problem
We do not look to external sources for why we didn't hit a deadline, meet an objective, etc. We hold ourselves responsible.
Intellectually honest and curious
We challenge each other's ideas daily - on product strategy and beyond. At lunch we are more likely to talk philosophy than TV (though we do some of that too)
Emotionally open and vulnerable
We talk about the ups and the downs of our lives outside of work and strive to have high authenticity interactions with each other.
We work hard to be an enduring company that paves the way for all sorts of applications which require structuring verbal conversational data at scale.
High quality bar, and always rising
We redo our work again and again until it's great. (can be frustrating in the moment but is ultimately extremely rewarding when we build things that are greater than we imagined they would be)
- Ruby on Rails
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