
Cloud Native ML Engineer
3 days ago
We are looking for a highly skilled MLOps engineer to join our team and contribute to the development of our cloud-native machine learning platform.
About the PositionThe ideal candidate will have a strong background in MLOps, machine learning pipelines, and model deployment, as well as hands-on experience with Kubernetes, MLflow, Pachyderm, and DVC.
This role will involve working closely with cross-functional teams to ensure seamless integration of machine learning models into our cloud-native platform.
Duties:- Design and implement a robust and scalable system for managing model deployments, training, and experiments.
- Develop and maintain a solution to track and manage live applications, including version control for models and datasets in production.
- Integrate Pachyderm to organize and track versioned layers (Application - Model - Data) for a unified view of deployment components.
- Implement version lineage tracking from application code through models and datasets to improve troubleshooting and facilitate system enhancements.
Skills Required
- Proven experience in MLOps, machine learning pipelines, and model deployment.
- Strong knowledge of MLflow and Pachyderm for model and dataset version control.
- Hands-on experience with Kubernetes for deployment management and scaling machine learning models.
- Familiarity with DVC (Data Version Control) and cloud storage solutions like AWS S3.
- Proficiency in version control practices for machine learning applications, models, and datasets.
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