Team purpose and mission
- Working embedded with Data Scientists and other engineers to develop, deploy, scale and maintain impactful Machine Learning solutions
- Helping data scientists and other engineers with Machine Learning and ML Platform & infrastructure related topics and questions. Increasing the level of ML engineering in the team.
- Monitoring, maintenance and troubleshooting of deployed solutions
- Contributing to our MLOps practices and liaising with the ML Platform team
- We have openings in multiple domains, such as personalisation & recommendations, search, logistics etc.
📍This role can be based in one of our tech hubs in Helsinki, Berlin or Stockholm, or you can work remotely anywhere in Finland, Sweden, Germany, Denmark, and Estonia. Read more about our remote setup here. If you live outside of these countries - not to worry! We provide relocation support to help you make your way to Finland, Germany or Sweden.
- You are experienced in end-to-end machine learning deployments and maintenance of deployed solutions and have at least 3+ years of experience in ML/MLOps.
- Furthermore, you bring solid experience in scaling and troubleshooting machine learning deployments to the table. You can help with the technical issues the teams encounter.
- A good understanding of ML and MLOps principles as well as Software engineering experience in Python should complete your profile.
- Ideally you also have experience in Docker, Kubernetes, Flyte, Seldon Core.
The position will be filled as soon as we find the right person, so make sure to apply as soon as you realize you really, really want to join us!
The compensation will be a negotiable combination of monthly pay and DoorDash RSUs. The latter makes it exceptionally easy to be excited about our company growing and doing well, as you’ll own a piece of the pie.
For any further questions about the position, you can turn to Product+ Talent Acquisition Partner - Michal Szafraniec