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
Requirements:
• Degree in Computer Science or related technical fields.
• Proficient in distributed, asynchronous and concurrent programming in Python/PySpark, Scala and/or Javascript
• 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