ML Engineer for Power & Energy Intelligence

Kpler; Paris (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Kpler is seeking a Machine Learning Engineer to design and deploy predictive models powering our global commodity, energy, and maritime intelligence platforms. You will work closely with Data Scientists, Data Engineers, and Product teams to bridge research and production.

The role emphasizes production-grade Python services, scalable ML pipelines, time-series data handling in PostgreSQL, and strong MLOps practices, with a focus on reliability and fast iteration.

Qualifications

• Two to five years of experience as a data-focused software engineer.
• Significant Python experience with large production codebases.
• Deep understanding of electricity-grid fundamentals.
• Experience with PostgreSQL or similar databases, data normalisation, and time-series/event data handling.
• Proven data science and ML research experience including statistics, hypothesis testing, training, evaluation, backtesting, tuning, and model selection.
• Practical experience in ML engineering with model and feature versioning.
• Experience with Git, code reviews, and Agile practices, with strong written and spoken English.

Responsibilities

• Architect and deploy ML pipelines for power market forecasting and electricity grid modeling.
• Bridge research and engineering by turning prototypes into production-grade Python apps.
• Manage time-series and event data systems; design PostgreSQL schemas for high-throughput data.
• Implement automated model training, backtesting, evaluation, tuning, and versioning practices.
• Write modular, well-tested Python code; participate in code reviews, CI/CD, and Agile delivery processes.

Skills

Python mastery

MLOps

Data engineering

English fluency

Git & CI/CD

Agile methodologies

DS & ML research

Tools

PostgreSQL

Docker

Kubernetes

Apache Airflow

Kubeflow

MLflow

Apache Kafka

Job description

Kpler is seeking a Machine Learning Engineer to design and deploy predictive models powering our global commodity, energy, and maritime intelligence platforms. You will work closely with Data Scientists, Data Engineers, and Product teams to bridge research and production.

The role emphasizes production-grade Python services, scalable ML pipelines, time-series data handling in PostgreSQL, and strong MLOps practices, with a focus on reliability and fast iteration.