Mlops Model Deployment Engineer
hace 1 semana
Role Overview
Founded in 2016, Quantexa has grown into a global company with a vision of enabling better decision making through better data-driven intelligence. Our Analytics teams build, deploy and maintain a wide range of AI models which underpin our platform, including expertise in emerging methods for Graph based model and NLP models. We are looking for a highly skilled MLOps Engineer to join our team, working on developing and maintaining the infrastructure and automation pipelines that support our machine learning models.
MLOps Responsibilities
Collaborate with data scientists to ensure smooth deployment of machine learning models into production environments. Automate the deployment of machine learning models using CI/CD pipelines and container orchestration tools like Kubernetes and Docker. Ensure proper model versioning, governance, and compliance using tools like MLFlow, Kubeflow, or DVC.
Pipeline Automation
Build and maintain data and model pipelines for training, validation, deployment, and monitoring. Develop automated processes for data validation, feature engineering, and model training. Integrate pipelines with distributed data processing frameworks (e.g., Spark, Kafka) to ensure efficient data handling for model training and inference.
Monitoring & Maintenance
Set up monitoring systems to track model performance and detect issues like model drift, triggering retraining when necessary. Work with cloud infrastructure to scale models and ensure high availability in production environments. Contribute to the troubleshooting and resolution of issues with models in production.
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