Informacje o stanowisku

• Ability to select appropriate algorithms based on the problem and data characteristics (volume, structure, etc.).
• Design and execution of modeling experiments, prototyping, and industrialization of solutions within the existing MLOps ecosystem on Azure Databricks.
• Co-development of a recommendation system for digital client communication and price sensitivity models.
• Evaluation of model performance and experimental results, including identification and resolution of quality-related issues.
• Efficient selection of cloud computing resources with consideration for performance and organizational cost optimization.
• Design of optimized data pipelines for inference processes.
• Model maintenance, including monitoring of statistical quality metrics and troubleshooting of MLOps-related issues within the platform.
• Providing technical guidance and support to the team in model development and knowledge expansion in the area of Machine Learning.
• Conducting testing and optimization of ML models and algorithms.
• Extending and improving existing ML libraries and frameworks.

• Minimum 5 years of professional experience as a Data Scientist, Machine Learning Engineer, or in a similar role.
• Proven experience working with the Databricks platform.
• Hands-on experience with MLflow for building experiments and deploying models to production.
• Strong understanding and experience with recommender system algorithms and their deployment.
• Excellent knowledge of machine learning and deep learning algorithms (neural networks), with solid qualifications in statistics.
• Experience in applying classification and regression methods, as well as unsupervised learning techniques.
• Strong programming skills in Python and PySpark, with practical experience in TensorFlow, PyTorch, and Scikit-learn.
• Ability to optimize processing for large-scale model training, with knowledge of distributed training methods considered an asset.
• Familiarity with MLOps best practices.
• Understanding of CI/CD principles and experience with version control systems (GIT).
• Higher technical education in Data Science, Computer Science, Statistics, Mathematics, or a related field.

• Ability to select appropriate algorithms based on the problem and data characteristics (volume, structure, etc.).
• Design and execution of modeling experiments, prototyping, and industrialization of solutions within the existing MLOps ecosystem on Azure Databricks.
• Co-development of a recommendation system for digital client communication and price sensitivity models.
• Evaluation of model performance and experimental results, including identification and resolution of quality-related issues.
• Efficient selection of cloud computing resources with consideration for performance and organizational cost optimization.
• Design of optimized data pipelines for inference processes.
• Model maintenance, including monitoring of statistical quality metrics and troubleshooting of MLOps-related issues within the platform.
• Providing technical guidance and support to the team in model development and knowledge expansion in the area of Machine Learning.
• Conducting testing and optimization of ML models and algorithms.
• Extending and improving existing ML libraries and frameworks.

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