Machine Learning Operations Engineer

Job content

Are you interested in bringing Artificial Intelligence to the next level: the human level? Then you will love working at Chatlayer!

Chatlayer is a part of Sinch and based in Belgium. At Chatlayer we develop an easy-to-use Conversational AI platform that lets our clients build and maintain even the largest and most complex bots, no coding required. We work on a global scale: Our Natural Language Processing algorithms can understand more than 125 languages out of the box, even if you trained it in just 1 language.

We are still just at the beginning. We are still aiming to improve our AI in many ways and we need a Machine Learning Operations (MLOps) talent joining the team to make it happen! As we are part of Sinch, the solutions you think of and the code you write will be appreciated by many users on a global scale: We have deployed our application across multiple regions and are onboarding new customers all over the world on a daily basis.

You will join the growth and experience team of Chatlayer which focusses on providing the best bot building experience. Our customers use our advanced Natural Language Processing (NLP) capabilities to build Machine Learning (ML) models that understand questions that are asked to the chatbot. However, they just add some example questions and with one click of the button, they expect to have a fully deployed ML model. That’s where you come in as our MLOps engineer.

With your work, all our customer’s ML models will be automatically deployed when they click the button, will be stable and scale under load. You will form a bridge between the DevOps engineers and the ML engineers to make sure that the newly developed ML models can be deployed efficiently and get the right infrastructure. You will have the freedom to bring your own ideas to the table and implement the latest technologies

We are looking for someone who wants to work on the intersection of DevOps, Python development and Machine Learning (ML). As this a new and emerging field, we are open to anyone who is skilled in one of those three areas and willing to learn the other ones. Being eager to learn new things and being able to quickly apply new technologies is a much more important skill.

• You have a few years of experience in software engineering, preferably in Python
• You have knowledge about how to put things in production: CI/CD pipelines, Helm charts, Docker, Kubernetes,...
• You have knowledge about Machine Learning concepts, the ML life cycle,...
• You are eager to learn, especially in the three areas mentioned above
• You take responsibility and ownership
• You like to innovate and challenge the status quo
• You are eager to communicate with people from different areas

You’ll stand out from the crowd if you have:

• Worked with Docker, Kubernetes, Argo CD/Workflows/...,
• Worked with Natural Language Processing frameworks such as Spacy, HuggingFace, RASA,...
• Worked with Machine Learning platforms from experimentation till deployment and monitoring: MLFlow, Vertex AI, Sagemaker, Kubeflow,..

About the recruitment process:

To help us place the right people in the right role, we believe in science-based and fair assessment methods.We follow a competence-based, structured interview process where your skills, experience and attributes relevant to the role and Sinch will be assessed. As part of our recruitment process, pre-employment testing is used to help us increase our hiring success by identifying the candidates that are most likely to thrive and be successful in the role.We acknowledge that there are two parties making a decision in this process and welcome you to ask any questions you may have at any stage of the proces