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).