Machine Learning Engineer - Purchase Risk Management (All Genders) | Berlin, Germany | Zalando SE

Position:	Machine Learning Engineer - Purchase Risk Management (All Genders)
Institution:	Zalando SE
Location:	Berlin, Germany
Duties:	Take end-to-end ownership for developing, deploying, and operating machine learning solutions for detecting, predicting, and managing purchase risks; Quick prototyping and spiking of machine learning models to assess their applicability for solving research, customer, and business problems; Tackle challenges for developing algorithms and running them efficiently on resource constrained platforms; Monitoring and optimizing machine learning infrastructure running on AWS and Databricks/Spark; Conducting (ad-hoc) exploratory analysis based on big (un-/semi-)structured data to discover new suspicious behaviors on our fashion platform
Requirements:	1-3 years of hands-on experience as a machine learning engineer, developing and productionizing machine/deep learning models in cloud environments (preferably AWS); Good proficiency in Python and related machine/deep learning frameworks, such as Pytorch, Tensorflow, Keras, etc; Expertise in machine learning infrastructure and tooling, such as Databricks, Spark, Flink, relational databases, AWS SageMaker, S3, EC2, Step Functions, Git; Experience with data storage, ingestion, and transformation, also including machine learning workflow orchestration

Text:	Machine Learning Engineer - Purchase Risk Management (All Genders) Take end-to-end ownership for developing, deploying, and operating machine learning solutions for detecting, predicting, and managing purchase risks; Quick prototyping and spiking of machine learning models to assess their applicability for solving research, customer, and business problems; Tackle challenges for developing algorithms and running them efficiently on resource constrained platforms; Monitoring and optimizing machine learning infrastructure running on AWS and Databricks/Spark; Conducting (ad-hoc) exploratory analysis based on big (un-/semi-)structured data to discover new suspicious behaviors on our fashion platform 1-3 years of hands-on experience as a machine learning engineer, developing and productionizing machine/deep learning models in cloud environments (preferably AWS); Good proficiency in Python and related machine/deep learning frameworks, such as Pytorch, Tensorflow, Keras, etc; Expertise in machine learning infrastructure and tooling, such as Databricks, Spark, Flink, relational databases, AWS SageMaker, S3, EC2, Step Functions, Git; Experience with data storage, ingestion, and transformation, also including machine learning workflow orchestration