ML OPS
1 week ago
8+ years of experienceinML Opsengineering or a related field.
Strong proficiency inPython, with experience inmachine learning librariessuch asTensorFlow,PyTorch,scikit-learn, etc.
- Extensive experience withML Ops frameworkslikeKubeflow,MLflow,TensorFlow Extended (TFX),KubeFlow Pipelines, or similar.
- Strong experience in deploying and managing machine learning models incloud environments(AWS, GCP, Azure).
- Proficiency in managingCI/CD pipelinesfor ML workflows using tools such asJenkins,GitLab,CircleCI, etc.
- Hands-on experience withcontainerization(Docker) andorchestration(Kubernetes) technologies for model deployment.
- Skills : SageMaker, PySpark, AWS Services ; Nice to have: MLOps
*Mandatory Competencies*
Data Science and Machine Learning - Data Science and Machine Learning - AI/ML
Data Science and Machine Learning - Data Science and Machine Learning - Python
Development Tools and Management - Development Tools and Management - CI/CD
Data Science and Machine Learning - Data Science and Machine Learning - Pytorch
Beh - Communication
DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - Containerization (Docker, Kubernetes)
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