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).