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7 days ago
We are seeking a skilled and motivated MLOps professional to help design, build, and maintain a centralized ML operations pipeline.
About the RoleThe ideal candidate will work with a variety of technologies, including MLflow, Kubernetes, Pachyderm, and DVC, to create a robust and scalable system for managing model deployments, training, and experiments.
This role will focus on version control for applications, models, and datasets, while improving visibility and control over the entire MLOps lifecycle.
Key Responsibilities:- Deployment Management:
- 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.
Technical Skills Required
- 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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