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Comping
Comping
51 – 200 Xodimlar
KonsaltingLogistikaMarketing
Comping is a software company developing cloud-based tools for eCommerce businesses. Its platform brings together analytics, marketing automation, and inventory management to help online retailers understand sales, engage customers, and manage stock.
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Kompaniyadagi ish o‘rinlari

Machine Learning Engineer (Hybrid, Croatia)

Build and deploy predictive and time-series models for Comping’s digital solutions. Monitor production performance and model drift, retrain models, and work with data engineers on data preparation.

HRXorvatiyaGibridTo‘liq stavkaJuniorO‘rta darajaTalab Qilinadigan Til: xorvatMashinaviy o‘qitish muhandisi
BulutKafkaPandasPySparkPyTorchScikit-LearnSQLTensorFlow

Tavsif

  • Develop, evaluate, and optimize predictive models, including time-series forecasts.
  • Deploy models to production and monitor their performance and drift, retraining them as needed.
  • Work with data engineers to retrieve and prepare data.
  • Lead model implementation from start to finish with support from the team lead.

Talablar

  • 2–5 years of hands-on machine learning experience
  • Strong knowledge of Python (Pandas, scikit-learn, TensorFlow or PyTorch, and XGBoost) and SQL
  • Experience deploying and maintaining machine learning models in production, beyond notebooks
  • Experience with time-series forecasting
  • A degree in computer science, mathematics, physics, or a related field, such as from FER or PMF
  • Ability to work independently and explain results clearly to non-technical stakeholders
  • Experience with IBM tools such as Cloud Pak for Data, Watson ML/OpenScale, or watsonx.ai, or similar machine learning platforms
  • Experience with model monitoring and management tools for drift and explainability
  • Knowledge of PySpark and big data ecosystems such as Cloudera, Kafka, or Impala
  • Knowledge of probabilistic forecasting
  • Knowledge of the energy sector or experience working with meteorological data

Imtiyozlar

  • Work on production machine learning systems from initial concept and first model through implementation, monitoring, and model management
  • Own the models you develop and influence technical decisions on the project
  • Funding for professional certifications, such as IBM watsonx.ai or Cloud Pak for Data
  • Opportunities to build expertise in MLOps, big data technologies, and the energy sector
  • Flexible working hours
  • Short Fridays, with work ending by 2 p.m.
  • 25 days of annual leave for all employees
  • A paid day off for your Comping work anniversary
  • Childcare subsidy
  • Financial gift for the birth of a child
  • A day off for parents on their child’s first day of school
  • Christmas gift for children
  • Financial St. Nicholas Day gift for children
  • One day off per month for parents of children with disabilities to attend appointments
  • Supplementary health insurance
  • Internal training
  • Professional development training
  • Conferences and events
  • Mentoring program
  • Team-building activities
  • Internal events
  • MultiSport membership
  • Support for charitable community initiatives

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