
Cloud Machine Learning Pipeline Architect
4 days ago
Leading a team of experts to develop and maintain robust machine learning pipelines is a vital part of our job. We need someone who can ensure efficient model deployment, monitoring, and lifecycle management within a cloud-based environment.
Responsibilities:- We are looking for an experienced MLOps engineer who can build and maintain scalable pipelines in GCP Vertex AI for end-to-end machine learning workflows.
- The ideal candidate will manage the full MLOps lifecycle from data preprocessing, model training, and deployment to model monitoring and drift detection.
- They should be able to implement real-time model monitoring and drift detection to ensure optimal model performance over time.
- We require expertise in building and executing CI/CD containerization and orchestration tools, including Jenkins, GitHub Pipelines, Docker, Kubernetes, and OpenShift.
- The successful candidate will optimize model training and inference processes using GPU accelerators and CUDA.
- They will collaborate with cross-functional teams to automate and streamline machine learning model deployment and monitoring.
- We utilize Python 3.10 with libraries like pandas, NumPy, and TensorFlow for data processing and model development.
- The selected candidate will set up infrastructure for continuous training, testing, and deployment of machine learning models.
- Ensuring scalability, security, and high availability in all machine learning operations is crucial by implementing best practices in MLOps.
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Senior Cloud Machine Learning Engineer
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AI/ML Machine Learning Engineer
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Architect, Machine Learning
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Cloud Solutions Architect
4 days ago
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Cloud Pipeline Architect
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Senior Machine Learning Engineer
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AI and Machine Learning Specialist
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Chief Architect
3 days ago
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