Machine Learning Engineer (Conversational AI)
- Experiment with, apply, and benchmark new NLP or Speech algorithms
- Productize cutting-edge research
- Deploy machine learning code in the cloud
- You actively keep your eye out for new and emerging machine learning solutions that might add value to the product and/or the customer.
- You bring your ideas to the table to make building human-like chat and voice bots a reality.
- You set up proof-of-concepts and bring those to the product.
We are a young and vibrant team where your input is not only appreciated but expected. We like doers that have a can-do mentality. Success is celebrated together, and we pride ourselves in the quality and innovativeness of our platform.
Who are you?
This job isn’t for everyone. If you don’t like collaborating, if you dislike communicating, if you just want to build what you are told, or if working on the cutting edge of machine learning isn’t your thing, that’s OK. But then we’re probably not the company for you. However, if you like to go the extra (s)mile and like to have impact on a cutting-edge product that can bridge the gap between AI and humans? Well, then we are definitely a good match!
In order to contribute in this role:
- You have a master’s degree in Computer Science or equivalent skills, complemented with an experience in NLP or Speech Recognition – we expect at least 2 years of experience in NLP or Speech
- You have solid and proven working experience and knowledge of Python
- You have working experience with Git and Git Flow
- You are fluent in English
- You are a good communicator, can work independently and take matters into your own hands.
- You have the ability to quickly learn new technologies and successfully implement them
Big plus!
You’ll stand out from the crowd if you have:
- Multiple language skills
- A multi-cultural mindset
- A PhD in Machine Learning
- Knowledge of conversational design/AI
- Put and maintained Machine Learning models in production
- Experience with one or more of the following libraries/technologies: PyTorch, TensorFlow, scikit-learn, spaCy, Docker, Kubernetes, C, C++.