We’re looking for a motivated machine learning engineer to join us at Rasa. The position offers the opportunity to have a huge impact at an early stage startup.
Our distributed research team has offices in Berlin, Germany and Edinburgh, UK so if you would prefer to work on site you can join either of those locations.


We are looking for a Senior Machine Learning Engineer with experience in Natural Language Processing who combines technical, communication, and analytical capabilities; who can architect and implement efficient algorithms in tensorflow; and who will have the opportunity to design and develop creative, compelling, and cutting-edge systems that support our mission.

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. Your work will be used by thousands of developers all over the world, and you’ll spend time with our community to get inspiration and feedback. We’re not here to chase SotA on established benchmarks. To ship machine learning products that really help our community, you’ll need to develop new machine learning tools that help developers build great conversational software, and enable them to build things that they can’t currently. You'll have to come up with good architectural designs, quality code, and break an ambitious long-term vision down into milestones and issues. For example, you should feel comfortable refactoring this code to accommodate different types of attention.

We do fundamental research, and we ship commercial quality software that puts it to use. Because engineering is so close to research, you’ll quickly learn a lot about research practice and translating it into working systems. You can check out some of our projects on our research page.

Please keep in mind that we are describing the background we imagine would best fit the role. Even if you don’t meet all the requirements, yet you are confident that you are up for the task, we absolutely want to get to know you!


  • You take pride in teaching and learning from teammates, and enjoy constructive peer review in a respectful environment
  • You're comfortable being lean and fix problems without waiting for someone to tell you to
  • You can effectively communicate what you’re working on with non-technical team members—from marketing and business development to UX design
  • When someone presents the results of an experiment, you ask questions that cut to the heart of the matter.

Technical requirements

  • Experience in designing and building complex machine learning systems for natural language processing applications
  • Experience communicating technical material
  • Advanced knowledge in Python or another programming language and at least one machine learning framework
  • Ability to think ahead and anticipate technological challenges
  • You love using machine learning to solve tough problems, and have demonstrable experience doing so
  • You are comfortable with the mathematics behind machine learning


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 a research system from an initial prototype all the way to a merged PR in our open source libraries.
  • Architect, code & test backend services to support machine learning training, prediction and annotation. 
  • Improve the scalability & performance of machine learning systems for our enterprise customers which are handling high loads
  • Collaborate with machine learning researchers to hone their engineering skills and processes
  • Speak to the Rasa community (developers who use our libraries) to help prioritize our research roadmap, and assess the impact of the research we’ve shipped.
  • Work on our open source projects alongside our large contributor base and community
  • Work with driven people across all areas of the company—from marketing and business development to machine learning research and UX design—to create the tools to let all makers build AI assistants that everyone can use


Rasa supplies the standard infrastructure for conversational AI, providing the tools required to build better, more resilient contextual assistants. With more than 10 million downloads since launch, Rasa Open Source is loved by developers worldwide, with a friendly, fast-growing community learning from each other and working together to make better text- and voice-based AI assistants.

Rasa offers three key products in its suite of conversational AI offering. Rasa Open Source is the most popular open source software in conversational AI. Rasa X, released in 2019, is a free toolset that helps developers quickly improve and share an AI assistant built with Rasa Open Source. Rasa Enterprise is the company's commercial offering, providing an enterprise-grade platform for developing contextual assistants at scale. Rasa runs in production everywhere from startups to Fortune 500s, and provides the data privacy and security needed to enterprises of every size.

Rasa is privately held, with funding from Accel, Andreessen Horowitz, Basis Set Ventures, and others. The company was founded in 2016 and has offices in Berlin, Germany and Edinburgh, United Kingdom.

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.

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DEI @ Rasa

With people from more than 20 nationalities and all continents working in five different countries, female & non-binary/genderqueer representation of nearly 50% in a male-heavy tech industry, and ages ranging from 21 to 60 years, our team is diverse in many aspects. But we believe there is much more we can do to make our company more diverse and inclusive and to contribute to a world that gives everyone fair opportunities.

To reach that goal, we have established a company target that 100% of roles have more than 50% of applicants from underrepresented groups. Recruiting is where diversity has to start. Of course, an inclusive company environment is necessary to attract diverse talent, and tracking and reporting our diversity metrics from the beginning will help us understand how we’re doing.

We are aware that diversity has many different dimensions but to start, we will be tracking gender and ethnicity, as it is measurable and concrete. To that end, we have started to ask all Rasa applicants to anonymously share diversity information. To remove our own bias, this data is held completely separate from the application and will be held in the highest confidence.

At Rasa, we consider our work on diversity, equity and inclusion to be an ongoing effort, and we welcome suggestions and comments. If you are happy to help us with our targets we would really appreciate you self identifying below. 

What is your Gender?

What is your racial identity?