Collaborate with Data Scientists, ML Engineers, Site Reliability Engineers, and Product Engineers to identify opportunities and work around constraints to deliver ML systems
Deploy, monitor, evaluate, and optimize production machine learning models in 24/7 customer-facing applications
Implement scalable and reliable systems to handle model inference at scale
Develop and maintain automated pipelines for model training, testing, and deployment
Improve CI/CD practices to enable rapid and reliable model updates to speed up iterative learning
Respond to alerts and troubleshoot issues related to model deployment and infrastructure
Design and develop robust endpoint APIs to enable software engineers across the product to integrate ML APIs into applications
Develop, deploy, maintain and extend new technologies to enable and enhance data scientists’ capabilities for every step of the ML model life cycle
Skills Required
Machine Learning
Python
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