Requirements:

📍Proven experience with ML frameworks and algorithms, including CatBoost, XGBoost, Neural Networks, and Random Forest. 📍Proficiency in building and maintaining ML pipelines for data preparation, model training, and deployment. 📍Experience with cloud platforms, particularly AWS, and working with Amazon Feature Store. 📍Strong programming skills in Python and familiarity with ML libraries such as Scikit-learn, TensorFlow, and PyTorch. 📍Solid understanding of data engineering concepts and tools. 📍Ability to work collaboratively with data scientists and data engineers to deliver scalable solutions. 📍Spoken English skills — your level should be no lower than Upper-Intermediate. 📍Strong analytical and problem-solving skills.

Responsibilities:

📍Develop, implement, and maintain robust data pipelines for training and retraining machine learning models. 📍Automate workflows to streamline data preparation and model deployment processes. 📍Design and deploy new features to the feature store, ensuring data quality and integrity, including backfilling historical data when necessary. 📍Collaborate with data scientists and analysts to translate requirements into scalable machine learning solutions. 📍Monitor and evaluate model performance, retraining models with updated data as needed to maintain accuracy and relevance. 📍Optimize existing ML models to improve efficiency and performance in production environments.