Machine Learning Engineer @ Scalac
Scalac
As a Machine Learning Engineer, you’ll be working on an external fintech project. By joining Scalac, you’ll become part of an organization rooted in the Nordic region, which offers a dynamic and innovative work environment and is an attractive workplace for those seeking to contribute to cutting-edge financial solutions.What benefits are waiting for you?
*or equivalent currency in USD or EURRecruitment process:
After technical steps, regardless of your evaluation, you will receive clear feedback from us!Wondering what else might await you at Scalac?
We’re a remote-friendly company from the very beginning, and on board, we have people from 13 different countries – from LATAM to Europe. Do you prefer to work from the office? We’ll be more than happy if you visit us in Gdańsk!
No comments at all. Join us and see for yourself! (you can also see a sample on our YouTube 😎)
You can join a place where Scalacers are open to exchanging experiences. They’re happy to share their knowledge and skills. We do this on dedicated channels on Slack or during Pizza Days meetings (where we also eat pizza together, no matter where we’re connecting from!).
From the very first day, we will take care of your development. Tell us about your goals that you want to achieve, and we’ll help you realize them through the development budget. You can also count on a dedicated mentor who will support you in the first months.
Feel like a part of the community thanks to our events – Functional World and ScaLatin. Exchange knowledge and experiences with industry peers during live online meetings. Do you want to inspire others? Become our speaker! ,[Keeping CP4D compliant, up-to-date and scalable (e.g. new storage solution)., The target AI architecture is a hybrid cloud, with CP4D playing a key role. We should leverage its capabilities more extensively, such as using OpenScale for monitoring, CP4D Feature store, CP4D WMLA, GPUs., Support increasing demand from business (e.g. Propensity, Customer Lifetime Value, Micro-segmentation, channel recommendation models).] Requirements: Scala, Spark, Machnine Learning, SQL, Hadoop, Hive, Spark SQL, T-SQL, Bitbucket, Git Additionally: Sport subscription, Training budget, Private healthcare, Flat structure, International projects, Integration events, Development budget, English lessons, Free coffee, Bike parking, Playroom, Shower, Free beverages, Free parking, In-house trainings, Modern office, Startup atmosphere, No dress code, Table Tennis, Foosball.
Gdańsk, pomorskie
Fri, 06 Sep 2024 22:27:55 GMT
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