As a Machine Learning Engineer you will be part of the team that shapes Mango’s data intelligence, strategy and architecture. You will develop scalable machine learning models and deploy MLOps capabilities to enable use cases that are very innovative in the retail space, such as geoanalytics, robotization, omnichannel personalization, the connected store, consumer 360º and real-time decisions.
We expect you to:
- Use Apache Spark, distributed and asynchronous programming to scale up new Machine Learning models in collaboration with data scientists and engineers
- Design the architecture and deploy the right components to ensure data science models are performant, scalable and loosely-coupled, leveraging AWS services such as Lambda, Kinesis, DynamoDB, API Gateway, etc
- Lead the development of frameworks and tools to facilitate code-reusability, API-fication of results, data drifting monitoring and other MLOps capabilities
- Stay connected to the latest developments in MLOps and invest time in bringing new use cases and improvements to Mango
• Degree in Computer Science or related technical fields.
• Experience in distributed computing (Apache Spark and libraries such as MLlib) and streaming technologies (Spark Streaming, Kinesis)
• Experience working with AWS services (e.g., S3, Lambda, DynamoDB, EC2, API Gateway) and continuous integration tools
• Understanding of Machine Learning algorithms
• Engineer by heart, hands-on mentality