Machine Learning Engineer (MLOps) - Search

The Search Relevance team, within Wolt’s Search department, owns the ML components of the Search’s stack that retrieve and rank restaurants, stores, dishes and items. Thanks to the team’s ML capabilities, Wolt can find the right results for a customer query in different touchpoints of our customers’ journey. 

As a Machine Learning Engineer in Wolt’s Search Relevance team you will:

• Develop, train, deploy and maintain retrieval and ranking models that will surface the right content for our customers’ queries;

• Work at Wolt’s scale: Wolt operates in 25 different markets with as many languages and millions of customers;

• Be part of a cross-disciplinary team with Data Scientists, Software Engineers and Analysts to provide solutions to customer problems with a direct impact on the company’s business KPIs;

• Build the team’s ML infrastructure and raise the team’s ML engineering excellence bar;

• Monitor, maintain and troubleshoot the Search Relevance’s ML stack;

• Contribute to our MLOps practices and liaise with Wolt’s ML Platform team.

📍This role can be based in one of our tech hubs in Berlin, Helsinki, 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 ML systems and have at least 3+ years of experience in ML/MLOps;

• You have deployed and ran ML models in production at scale;

• You bring solid experience in scaling and troubleshooting machine learning deployments to the table. You can help with the technical issues the teams encounter;

• Good understanding of ML and MLOps principles as well as Software engineering experience in Python should complete your profile;

• Experienced in Docker, Kubernetes, workflow orchestration tools (e.g. Flyte), model and experiment registries (e.g. MLflow) and model serving systems (e.g. Seldon);

• Domain experience in Search and/or Personalization is a plus.

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 - Fernanda Prado e Silva ([email protected]).