HP ENTERPRISE SERVICES
HPE Ezmeral is an enterprise-grade solution that accelerates customers journey from hybrid to cloud through its unified container platform. This solution is designed for cloud-native and non-cloud native applications that allow the customer to run on any infrastructure: either on-premises, in multiple public clouds, in a hybrid model, or at the edge. Combining 100 PERCENT open-source Kubernetes with unique software innovations and integrated persistent storage technology, customers can now modernize existing enterprise applications without re-architecting. This software provides an enterprise-scale Kubernetes-based platform specialized to run Machine Learning and Deep Learning applications and tools.
How You'll Make Your Mark:
We are seeking a talented ML Infrastructure Engineer to design and enhance HPE Ezmeral MLOPs. The candidate will design and build ML infrastructure solutions on Kubernetes, stretching the entire spectrum of ML operationalization from data pre-processing, storage, feature engineering, model training, hyperparameter tuning, deployment, and model management while addressing challenges pertaining to security, scaling, performance and usability. The candidate will be exposed to a broad variety of emerging AI/ML infrastructure tools like Kubeflow, Airflow, Tensorflow, Mlflow, Model dB, etc
Bachelor's or Master's degree in Computer Science, Information Systems, or equivalent.
Typically 4 years experience.
Strong programming skills in one or more of the following languages Python, Golang, Java, Scala
Experience in building, managing, deploying, and debugging containerized solutions.
Experience working with Machine Learning / Deep Learning Platforms and Infrastructure in production and at scale
Basic understanding and exposure to various aspects of ML systems like Model Training, Inferencing, Feature Engineering, hyperparameter tuning etc
Passionate about highly distributed systems, and all things containerization
Familiar with the inner workings of Kubernetes, and/or perhaps similar container system
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