ML Engineer – Power

About This Opportunity

We are representing a confidential energy intelligence organization seeking an ML Engineer to join their Power team in Paris. Our client transforms complex commodity and maritime data into real-time insights that support critical decision-making for trading firms and industrial leaders worldwide.

As an ML Engineer, you will architect production-grade machine learning systems for power market forecasting and electricity grid modeling. This role bridges data science research and scalable software engineering, requiring both technical depth and practical delivery excellence.

Responsibilities

• Design, build, and maintain production ML pipelines and microservices for power market forecasting and electricity grid modeling
• Transition statistical and machine learning prototypes from experimentation into scalable, production-ready Python applications
• Design and optimize PostgreSQL database schemas to handle high-throughput time-series data, event streams, and normalization routines
• Establish automated model training, backtesting, evaluation, tuning, and feature/model versioning standards
• Construct clean data ingestion and transformation pipelines ensuring high integrity, validation, and low-latency access
• Write modular, well-tested Python code and participate actively in peer code reviews, CI/CD automation, and Agile delivery

What We're Looking For

Must-Have Qualifications:

• Approximately 2-5 years of experience as a data-focused software engineer
• Significant experience working with large production Python codebases (beyond notebook work)
• Deep understanding of electricity-grid fundamentals, including generation, transmission, and electricity markets
• Experience in data engineering with PostgreSQL or similar databases, including database design, data normalization, and managing time-series and event data
• Proven experience in data science and machine learning research: statistics, hypothesis testing, model training, evaluation, backtesting, tuning, and model selection
• Practical MLOps experience including model and feature versioning
• Confidence working with Git, code reviews, and Agile methodologies
• Strong written and spoken English

Nice-to-Have Qualifications:

• 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 like Apache Kafka

How We Work With You

Our talent team at Get A Job.ai partners exclusively with this client to identify exceptional ML engineering talent. When you apply through our platform, a dedicated recruiter will conduct an initial screening to understand your background and ensure alignment with the role requirements. We then submit qualified candidates directly to our client for consideration.

Please note: all applications must come through Get A Job.ai. We ask that you do not attempt to contact the client directly, as this allows us to best represent your candidacy and provide you with guidance throughout the interview process.

Pay

Compensation details will be discussed during the screening process with our recruiting team.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices. We welcome candidates of all backgrounds, experiences, abilities, and perspectives. Research shows that some candidates may not apply unless they meet 100% of qualifications—we encourage you to apply if this role excites you, even if your experience doesn't perfectly align with every requirement listed.