Description
Aufgaben:·The MLOps engineer should be able to implement MLOps architectures on on-premise and hyperscaler environments in an enterprise context
Must-Have-Skills:
·General understanding of data science is crucial as MLOps engineers work closely with data scientists and machine learning models
·Experience in at least one cloud platform (preferably AWS) and subsequent services within that platform
·Proficiency in Python/R programming is essential, C++ is an advantage
·Knowledge of SQL
·Linux/Unix shell scripting
·Best practices regarding CI/CD
·Solid knowledge of account segmentation on hyperscalers
·Ability to implement all aspects of a MLOps platform
Frameworks:
·Machine Learning Frameworks: Knowledge of frameworks such as Keras, PyTorch, Tensorflow is often required
·MLOps Frameworks: Experience in using popular MLOps frameworks like Kubeflow, MLFlow, and DataRobot is beneficial
·Proven ability to integrate cross-platform and microservice based architecture frameworks on any given infrastructure
·Experience in using and maintaining open-source frameworks is advantageuos
Start: 06.05.2024
Dauer: 8 Monate
Einsatzort: Remote 100%
Branche: EDV-Dienstleistungen
Auslastung: 100%