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.
Сипаттама
- 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.
Талаптар
- 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
Артықшылықтар
- 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
