Senior Machine Learning Engineer II
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Die Stelle
Design and implement scalable ML infrastructure using Ray to support model training, deployment, and inference at scale.
Leverage Kubernetes to orchestrate containerized applications and manage ML models and services.
Develop and maintain CI/CD pipelines for automated testing, deployment, and lifecycle management of ML applications.
Implement robust monitoring, logging, and alerting to ensure high availability, performance, and security of the ML platform.
Collaborate with data scientists and ML engineers to optimize data pipelines and model performance, while staying current with ML advancements and best practices.
Provide DevOps/SRE support, incident response, performance tuning, disaster recovery planning, and promote a customer-focused, long-term, and inclusive culture.
Leverage Kubernetes to orchestrate containerized applications and manage ML models and services.
Develop and maintain CI/CD pipelines for automated testing, deployment, and lifecycle management of ML applications.
Implement robust monitoring, logging, and alerting to ensure high availability, performance, and security of the ML platform.
Collaborate with data scientists and ML engineers to optimize data pipelines and model performance, while staying current with ML advancements and best practices.
Provide DevOps/SRE support, incident response, performance tuning, disaster recovery planning, and promote a customer-focused, long-term, and inclusive culture.
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