Machine Learning Engineer Senior

📋 Description Develop and optimize ML models, ensuring scalability, monitoring, and MLOps integration. Implement client requirements from EDA to feature engineering and model lifecycle management. Build ML POCs to validate and refine solutions. Optimize models for performance, latency, memory, and throughput. Design and maintain feature stores and data pipelines for ML workflows. Research and implement emerging ML/AI techniques to enhance solutions. 🎯 Requirements ML systems with lifecycle management, monitoring, and MLOps pipelines. Python stack: Pandas, NumPy, Jupyter, Scikit-Learn, XGBoost, Plotly; SQL. Cloud platforms: AWS, GCP, Azure. ML workflows: Airflow, MLflow, Databricks, or similar. Deep learning frameworks: Keras, PyTorch, TensorFlow; Docker basics. 🎁 Benefits Remote-first culture – work from anywhere. In-Company English Lessons. Wellhub or sports club stipend to stay active. AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered. Food credits via Pedidos Ya. Birthday off + an extra vacation week (Mutt Week).