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The machine learning team is undergoing a metamorphosis as we embark on promoting Embedded ML capabilities as a key differentiator in the Splunk platform. Our new initiatives span from new developer focussed platform capabilities such as Splunk Machine Learning Environment (smle), to Streaming ML based novel solutions and algorithms crafted for Splunk use cases, to ML-powered experiences that improve premium Splunk Apps.
In the machine learning group at Splunk we work on some of the most challenging machine learning problems involving logs and metrics and applying machine learning methods to domains like Security, IT and Observability. Solution architects for the machine learning group help position these new initiatives with customers; prototype use cases and solutions using these technologies; collect feedback to help refine engineering requirements and craft GTM motions; identify and cultivate new opportunities where ML can improve customer experiences; and help evangelize upcoming ML product initiatives. This role is distinct in cutting across engineering, product management, research and customer facing responsibilities.
In this particular opportunity, we are looking for a Solutions Architect to evangelize and lead the adoption of Smle (Splunk Machine Learning Environment). The candidate is encouraged to engage with the user community to train them and evangelize Smle, meet with customers to suggest solutions that they can build with the technology, and see customers through implementing and fixing data science workflows on Smle. They are also responsible for producing and detailing sample workflows for various common machine learning tasks of interest to Splunk customers.
Our data science platform Smle is purpose built for simplifying the development and deployment of machine learning models for both internal and external data scientist use cases around these domains. Our customers challenge us with interesting machine learning use cases and requirements. As the complexity grows for both us and our customers, we are looking to our Solutions Architects to fully understand the architecture that powers Smle and how various use cases can be implemented on them. Our Solutions Architects not only work with open source technologies such as Apache Flink, Apache Pulsar, Jupyter but they also recommend product features and contribute to the open source community.
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