MachineLearningPlatformEngineer

In a nutshell You’ll work on building the tools and infrastructure to help our Machine Learning Engineers build and productionize robust machine learning models. Working closely with ML Engineers, you’ll identify opportunities to improve the machine learning lifecycle at Picnic. From tools that improve model experimentation, to automations that simplify model deployment. You will collaborate with other platform teams at Picnic to make sure our tech stack remains aligned with the rest of the Tech team, while building and integrating the solutions that solve the problems unique to machine learning systems. Check out some of our previous machine learning projects here: https://blog.picnic.nl/tagged/machine-learning Tricks of the trade Various MLOps-oriented projects to: Automate machine learning model retraining and deployment Set up infrastructure for model inference, supporting deployment strategies like A/B testing and shadow testing. Improve monitoring in order to exercise operational excellence for our machine learning models. Simplify and standardize usage of tools by developing and inner-sourcing Python packages Your contributions to the platform will power: Recommendation systems: generating useful in-app grocery suggestions for our customers. LLM use cases: automate systems to categorize Customer Success tickets. Outlier detection: low-latency decision support systems to prevent fraud. Time-series forecasting: improving the operational efficiency throughout our supply chain, from our automated fulfilment center to our last mile delivery. You will definitely: Work closely with ML Engineers to identify opportunities, define use cases, and scope out the requirements Own your own project from inception to production Experiment with and evaluate new technologies Develop tools and enhancements for our ML Platform We’re looking for Master’s degree or higher in AI, Computer Science, or a related field 2+ years of experience in productionizing machine learning models,