Running a flexible Machine Learning engine at scale is hard. We must ingest and process large volumes of data uninterruptedly and store it in a scalable manner. The data needs to be prepared and served to hundreds of models constantly. All the predictions of the models, as well as other data pipelines, must be stored and reachable for our web application(s) to present the generated insights to our customers.
We work on the system that delivers this functionality and also allows the Machine Learning engineers to deliver new and improved models at ease, manage existing models, monitor these models, and many different interactions, all of which are crucial to day to day operations.
You will be working and interacting with a wide array of technologies that constitute Jungle's core systems (data handling/processing, serving ML models, etc...) and building the backend systems that provide access to all this functionality. You will have the possibility to work on and enhance the different stages of an end-to-end Machine Learning system at scale, with a focus on the initial steps of the entire pipeline: data ingestion.
Who we are
Jungle develops and applies Artificial Intelligence to increase the uptime and performance of renewable energy sources. Built on existing sensors and data streams, the company’s technology enables solar and wind energy owners to squeeze more out of their assets, accelerating the world’s transition to renewable energy sources.
We have productised our services into a web application and are continuously improving it to ensure that our best analyses and visualisations help our users get the maximum energy out of their assets. We operate at a large scale - millions of data points per day - providing always-on predictive models, alarms and metrics visualisations for some of the largest and most sophisticated customers in the global renewable energy space. This is not your average dashboard, we’re talking about intelligently visualising handling large quantities of data to drive performant visualisations and functionality.
Why do we need you?
Why work with us?
Preferred Requirements (extra)
About you
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