Ezmeral ML Infrastructure Engineer at HPE in Santa Clara, California

Job Description:

Ezmeral ML Infrastructure Engineer

Job Description:

Hewlett Packard Enterprise advances the way people live and work. We bring together the brightest minds to create breakthrough technology solutions, helping our customers make their mark on the world. HPE makes Hybrid IT simple. HPE helps customers to design the right mix of Hybrid IT to serve their unique needs. We bring next generation infrastructure that uses intelligent software to simplify and accelerate the delivery of new apps, services, and business insights. Providing new ways to deliver and manage IT on-premises and in the cloud.

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% 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

About You:

• 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




• Familiarity with Kubernetes Operators or Helm Charts will be a huge plus

What We Can Offer You:

Extensive benefits, a competitive salary and participation in the shared values and purpose that make Hewlett Packard Enterprise one of the world´s most attractive employers! At HPE, our goal is to provide equal opportunities, flexible work-life balance, and constantly evolving career growth.

If you are looking for challenges in an exciting, supportive and international work environment, then we definitely want to hear from you. Continue the conversation by clicking apply now below, or directly via our Careers Portal at www.hpe.com/careers. 

Join us and make your mark!

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HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT and Affirmative Action employer. We are committed to diversity and building a team that represents a variety of backgrounds, perspectives, and skills. We do not discriminate and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global diverse team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together.

Job:

Job Level:

Hewlett Packard Enterprise is EEO F/M/Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to the use of arrest and conviction records, including the San Francisco Fair Chance Ordinance and similar laws and will consider for employment qualified applicants with criminal histories.