Senior ML/Data Engineer @ emagine Sp. Z o.o.

6 godzin temu


Gdynia, Polska emagine Sp. Z o.o. Pełny etat

PROJECT INFORMATION:
Industry : banking
Location : hybrid work (1 day a week from the office in Gdansk or Gdynia)
Remuneration : up to about 180 PLN/H net + VAT
Start : ASAP (to be agreed)
Project duratio n: long term
We are seeking an Senior ML/Data Engineer to enhance hybrid cloud architecture, where Cloud Pak for Data (CP4D) plays a central role.

Minimum  3 years  of experience in training, testing, and implementing  ML models.
Advanced  proficiency in SQL  (T-SQL, PL/SQL, Spark SQL) with at least  3 years  of experience.
A minimum of 2 years working with  Apache Spark  for big data processing.
Experience with the  Hadoop ecosystem  (Hadoop, Hive) and handling large volumes of data in near real-time.
At least 1 year of experience working with  Scala  and  MLOps  practices.
Familiarity with version control strategies, particularly GIT or Bitbucket
PROJECT INFORMATION:
Industry : banking
Location : hybrid work (1 day a week from the office in Gdansk or Gdynia)
Remuneration : up to about 180 PLN/H net + VAT
Start : ASAP (to be agreed)
Project duratio n: long term
We are seeking an Senior ML/Data Engineer to enhance hybrid cloud architecture, where Cloud Pak for Data (CP4D) plays a central role.
,[Design and Implementation of ML Models: Develop and implement machine learning models such as Propensity, Customer Lifetime Value, Micro-segmentation, and channel recommendation models. You will collaborate with use case teams to streamline training and deployment processes, aiming to reduce time-to-market for AI solutions., MLOps Optimization: Enhance our current MLOps practices and frameworks, making them applicable to a broader range of use cases beyond propensity models. You will leverage CP4D’s standard capabilities and cloud infrastructure to ensure scalability., Cloud Enablement: Assist in preparing our AI/ML systems for future cloud integrations, maximizing the use of CP4D features such as Open Scale for monitoring, CP4D Feature Store, WMLA, and GPUs.] Requirements: ML models, SQL, Spark SQL, Apache Spark, Hadoop, Scala, MLOps, Git, Bitbucket Tools: Jira, Agile, Scrum. Additionally: Sport Subscription, Private healthcare, Integration events.



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