
Machine Learning Operations Specialist
3 days ago
Effective machine learning operations is crucial to deploying, monitoring, and scaling machine learning models.
Key Responsibilities:
- Deploying, monitoring, and scaling ML models on cloud platforms such as AWS or GCP.
- Building and maintaining Continuous Integration/Continuous Deployment pipelines for ML workflows using tools like GitHub Actions or Jenkins.
- Containerizing and orchestrating workloads with Docker and Kubernetes, while managing infrastructure via Terraform.
- Implementing model registries, feature stores, and observability using tools like MLflow and Prometheus.
- Collaborating with data scientists to operationalize ML models for applications such as personalization and natural language processing.
Required Skills:
- Proficiency in Python and popular ML frameworks like Scikit-learn and TensorFlow.
- Experience with data pipelines such as Airflow and SQL.
Bonus Experience:
- Real-time ML serving and A/B testing.
Nice-to-Have:
- Knowledge of experiment design and causal inference.
Education:
- Bachelor's or Master's degree in a relevant field.
Benefits:
- The opportunity to shape the future of machine learning operations.
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