Rasa is the leading open source machine learning toolkit. Our software lets developers expand bots beyond answering simple questions, via natural language understanding.
We’re looking for extraordinary machine learning researchers to join us at Rasa.
ABOUT THIS ROLE
We don’t draw a hard line between our research and engineering teams, we all work on the same stack and share work, knowledge, and tools. The driver for our research is this: what would help developers build great conversational software? How can we enable them to build things that are currently out of reach? The primary outcome of our research is new features in the open source Rasa Stack. We also write papers but that’s secondary to the code output.
Machine learning research at Rasa is not about tweaking architectures until you get state-of-the-art results on an established dataset. You’ll have to come up with new questions to ask, new experiments to conduct, and break an ambitious long-term vision down into measurable milestones. Your work will go into libraries used by thousands of developers all over the world.
We do fundamental research, and we ship commercial quality software that puts it to use. We mostly work in Python, but dip into other languages when it makes sense to. Because research is so close to engineering, you’ll quickly learn a lot about APIs, Docker, deployment, continuous integration, and what it takes to write production code.
THINGS YOU WILL DO
We’re a startup, so you’ll have to be comfortable rolling up your sleeves and doing whatever is required to support our mission. However, you can definitely expect to:
Take research from an initial idea all the way to a merged PR in our open source libraries
Speak to the Rasa community (developers who use our libraries) to prioritize our research roadmap
Design and conduct experiments that bring us closer to our vision
Collaborate on research papers
When someone presents the results of an experiment, you ask questions that cut to the heart of the matter.
You take pride in teaching and learning from teammates, and enjoy constructive peer review in a respectful environment.
You can effectively communicate what you’re working on with non-technical team members and work with people across all areas of the company—from marketing and business development to UX design.
You love using machine learning to solve tough problems, and have demonstrable experience doing so.
You are comfortable with the mathematics behind machine learning.
Publication record in research venues in machine learning, NLP or related areas.