#Julia #Back-end #Algorithmic Development #Syntactic Loop Fusion #SIMD #MapReduce #Parallel Computing #Machine Learning #InstantML
As a Julia back-end developer at Tangent Works you will work on building the back-end components of a distributed machine learning system TIM (Tangent Information Modeller).
TIM is an automatic model building engine for forecasting and anomaly detection on time-series data. TIM introduces InstantML – a new perspective on machine learning that brings ML closer to the end user and is a next step after AutoML. From technical perspective, TIM is a set of distributed micro-services written in Python and Julia with REST APIs deployable on premise, in the cloud and on the edge. Front-end components are implemented using ReactJS. Some of the components are exposed via plug-ins to widely recognized BI platforms like Qlik, Alteryx, PowerBI, … and cloud platforms like Azure and Amazon.
We are looking for a self-motivated Julia back-end developer of machine learning strategies ideally with a 3+ years of relevant experience in developing algorithms using Julia. Successful candidate will be responsible for implementation, performance engineering, testing, and deployment of various modelling strategies in Julia. Knowledge of cloud computing and distributed computing is a plus. The candidate should also have an appropriate knowledge of statistical modelling so that he/she is able to study, understand and implement an algorithm with a limited amount of supervision. Knowledge of Python is also a plus.
You will work with a team of mathematicians on the developing of new features for the TIM Engine to deliver a performant, robust, scalable SaaS engine that is used in BI and Analytics platforms such as Qlik, PowerBI, Alteryx, …
This is a dream job for people passioned about code that drives machine learning to the next level.
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