Founding Product Engineer - Listen Labs
Posted 893 days ago, which is unusual. The employer's own board was still carrying it when we last read it, 2 hours ago.
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 4h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 893d ago
The date the source published, not the day we noticed it (2024-04-04). Last seen at its source 2h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
San Francisco
The description states no restriction of its own. This is the source's own tag.
Pay
$150k–200k/yr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
ashby employer's own board first seen 11d ago · last seen 2h ago
The listing
Everyone hates surveys. They’re tedious to fill out and give shallow data. That’s because they’re only a proxy for the real thing: conversations. Through a conversation, you can ask follow-up questions and get deep insights in a way that’s fun for the interviewee. Except you can’t have 1:1 conversations with everyone…
Listen Labs has built an AI interviewer that can ask follow-up questions, like a conversation, but at the scale and ease of use of a survey.
Technical Challenges
Turn qualitative data into quantitative insights
Listen Labs clusters free-form conversation into a structured format. This is not a trivial task. We use embeddings, fine-tuned large language models, and more to solve these problems.
Ask the right questions
Having a great conversation is not trivial. We’re fine-tuning and prompting in novel ways to get the right output from LLMs.
Multi-modality
We’ve built the fastest speech-to-speech pipeline but there’s a number of challenges we need to address to make it better. Our interviewer has audio input and output to the LLM and that’s tricky to get right.
Investors
There’s been $30B+ of market cap created from bringing surveys online. Our partner at Sequoia, [Bryan Schreier](https://www.sequoiacap.com/people/bryan-schreier/), was the first investor in Qualtrics – the $12B survey company.
About you
You love working on products end-to-end without detailed direction
You want to work in Next.js, TypeScript, and large language models
You are a collaborative builder and like to build systems with other engineers in mind.
You are an excellent written and verbal communicator.
You know when to seek assistance, and it's typically to discuss tradeoffs.
You don't scoff at unglamorous engineering tasks, yaks don't shave themselves.
Highly technical
Interested in building products end-to-end and owning the user experience
Excited about large language models
What we offer
$150,000 - $200,000 USD in cash.
High equity grant even for an early stage startup.
Work in person in our office @ 425 2nd St in San Francisco.