Back to all jobs

ML Product Success Engineer

Permanent employee · Berlin

About us

Rasa is the leading open source machine learning toolkit that lets developers expand bots beyond answering simple questions. Our open source Rasa Stack enables thousands of developers worldwide from startups to Fortune 500 to build in-house conversational AI (e.g. sophisticated chatbots and voice assistants) without hiring a big research team. Rasa Platform, a paid product, makes it simpler to train our machine learning models across multiple enterprise functions, allowing for faster iteration cycles.

The company is headquartered in Berlin (Germany), funded by Basis Set Ventures, Techstars and open source entrepreneurs such as Ross Mason (Founder of MuleSoft) and John Newton (Co-founder of Alfresco).


Rasa is an equal opportunity employer. We are still a small team and are committed to growing in an inclusive manner. We want to augment our team with talented, compassionate people irrespective of race, color, religion, national origin, sex, physical or mental disability, or age.

meta
Our commercial product Rasa Platform is growing quickly, and the number of companies building production systems with Rasa is increasing fast. We are looking for enthusiastic product success engineers to support us in helping those teams succeed. Doing this well is core to the success of the company.
About this role

Tens of thousands of developers worldwide build voice and chat systems with Rasa. 

You will be working directly with developers and product managers at companies using Rasa to build products. You’ll support them in development, analyzing use cases, testing and resolving issues. 

You will collaborate closely with Rasa’s product engineers to improve APIs and usability.

About you

You are excited about conversational software and letting people interact with machines through text and speech. You have experience programming in a couple of languages. You’re good at finding the root cause of a bug, and can find a solution or workaround when the obvious fixes haven’t worked. You’ve also worked on some practical applications of machine learning.  

You want to learn more about machine learning and natural language processing, applied machine learning, and putting AI systems into production.

Requirements:

  • Degree in computer science or a related field, or at least 2 years experience developing software.

  • Familiarity with machine learning concepts

  • Experience teaching & communicating technical material

  • Practical experience applying machine learning

Nice to have:

  • Experience applying NLP

  • Experience building chatbots or voice apps

Things You Might Do
  • Help our customer's engineers build ML-based bots and assistants with Rasa

  • Be the voice of our customers in product discussions, using what you’ve learned from helping them succeed to make our products more usable and valuable

  • Support product teams in identifying use cases for a chatbot or voice assistant

  • Report back when a customer encounters shortcomings in our products and discuss how to improve them with our product and applied research team

  • Run a workshop on best practices with the Rasa stack

  • Collaborate with product teams to make our open source libraries easier to use

Your application

Please answer the following questions in your cover letter:

Why you're applying for this position?
Something you've built and why you're proud of it?
What is the most frustrating interface that you used?

Please upload any documents that you want to include with your application. CV and cover letter are required.