Poland | Data and MLOps Engineer 1
Tasks
- Apply prescriptive analytics
- Build supervised learning models
- Build unsupervised learning models
- Conduct predictive maintenance analysis
- Conduct proof-of-value studies
- Create reusable ML frameworks
- Deploy machine learning models
- Design machine learning models
- Detect anomalies in data
- Develop computer vision models
- Develop data pipelines
- Forecast time series
- Integrate models with enterprise systems
- Operate model monitoring
- Optimize industrial processes
- Optimize models and parameters
- Perform feature engineering
- Perform rapid prototyping
- Support continuous model improvement
- Train deep learning models
- Use reinforcement learning
Perks/Benefits
Skills/Tech-stack
APIs | AWS | Anomaly Detection | Azure | CI/CD | Cloud Computing | Cloud platform | Computer Vision | Databricks | Deep learning | ELT | ETL | Feature Engineering | Forecasting | Google Cloud | Google Cloud Platform | Language Models | Large Language Models | MLOps | MLflow | Machine Learning | Matplotlib | Model Monitoring | Optimization | PyTorch | Python | Reinforcement Learning | SQL | SciPy | Scikit-learn | Series analysis | Supervised Learning | TensorFlow | Time Series | Time Series Analysis | Unsupervised Learning | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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