ML Engineer - Power

📋 Description Design, build, and maintain production-grade machine learning workflows and microservices for power Transition statistical and machine learning prototypes from initial experimentation into scalable Design and optimize database schemas in PostgreSQL to handle high-throughput time-series data Establish automated model training, backtesting, evaluation, tuning, and feature/model versioning Construct clean ingestion and transformation pipelines, ensuring high integrity, validation, and Write modular, well-tested Python code, actively participating in peer code reviews, CI/CD 🎯 Requirements Approximately two to five years of experience as a data-focused software engineer. Significant experience working with large production Python codebases, rather than working Deep understanding of electricity-grid fundamentals, including generation, transmission, and Experience in data engineering, including working with PostgreSQL or similar databases, database Proven experience in data science and machine learning research, encompassing statistics Practical experience in machine learning engineering, specifically including model and feature 🎁 Benefits Experience deploying ML workloads on AWS or GCP using Docker and Kubernetes. Familiarity with orchestration tools such as Apache Airflow, Kubeflow, or MLflow. Exposure to real-time streaming architectures (e.g., Apache Kafka).