Hello!
We're Happy Scribe, a 100% bootstrapped and profitable startup based in Barcelona, on a mission to make the internet accessible.
We offer transcription and subtitling services that combine AI with the expertise of language professionals to create a 5-star product.
We're working on one of the fundamental problems of this decade: speech-to-text technology.
We're 30 people at the moment, but growing fast and profitable, and we're building the team thoughtfully and with a lot of care.
For decades, transcription at scale has been almost impossible; now with the advancement of ASR technology, we are on the verge of having computers that understand speech better than humans.
Today, almost all the infrastructure is in place, but we'll need remarkable engineering to pull it off.
What will be your mission as an ML Engineer at Happy Scribe? Depending on your profile and career development preference, the nature of your work will vary a bit between improving infrastructure, improving our current AI models, or developing new ones.
Some mission examples could be:
Build the scalable infrastructure needed for the transcription of the future — like identifying coupling and extracting concerns into small and scalable services. Push forward the state of the art of AI models — improve quality of deep learning models such as: speech-to-text, speaker recognition, transcription to subtitling conversion, computer vision. Streamline Machine Learning operations — such as tools to automatically update our models, benchmark competitors or automate everyday tasks. Improve the performance, reliability, and efficiency of our systems — for example, finding bottlenecks in the transcription pipeline and optimizing them to reduce overall turnaround time. This might be for you if... You have 2+ years of experience as a Machine Learning Engineer (or researcher) or you have 2+ years experience as a Software Engineer with ML knowledge. You are passionate about Deep Learning, you are up-to-date with the latest research, and you have strong foundations of the mathematics behind it. You're product focused.
You want to listen to customers, and build the product that will solve their needs. You care about the business implications of anything you build.
You don't go after the shiny stuff, but see it as a balance of craft, speed, and the bottom line. You love steep learning curves, and are not afraid to learn about subjects that are outside of the comfort zone.
For example, you can learn most technologies as you go.
You're pragmatic about them; it's about the tools and tradeoffs, not ideologies. You care about information security and design things with security in mind. You are excited about our engineering principles.
Or at least curious about them, if they seem very different from what you've been doing in the past. You're a great mentor, able to share your knowledge and upskill other team members.
#J-18808-Ljbffr