Production ML Engineer - MLOps, Databricks & AWS

Eneco; Rotterdam; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Eneco is building reliable, production‑grade machine learning systems within the Energy Management Systems domain in Rotterdam. The role focuses on delivering scalable ML pipelines, MLOps tooling and platform improvements across Databricks, MLflow and AWS.

You will work with Data Scientists, Data Engineers and Software Engineers to productionize models, monitor performance and continuously improve deployed solutions, while mentoring peers and contributing to a culture of collaboration and

Qualifications

• 4+ years of professional ML engineering experience with a focus on production systems.
• 2+ years owning MLOps or production ML platforms.
• Hands-on Databricks for large-scale data processing and model training.
• Production ML with MLflow for experiment tracking and model registry.
• Strong AWS experience deploying and operating ML workloads.
• Proficiency in Scala for data processing and Spark-based ETL; JVM familiarity.
• Experience building CI/CD for ML and containerized deployments (Docker/Kubernetes).
• Knowledge of model monitoring, A/B testing and drift detection.
• Solid software engineering fundamentals with strong documentation and tests.
• Excellent communication and collaboration in multidisciplinary teams.

Responsabilités

• Design, build and maintain end-to-end ML pipelines for training, validation and production inference.
• Develop scalable MLOps capabilities, including CI/CD, testing, versioning and rollback strategies.
• Build and operate Databricks-based data processing and ML workflows at scale.
• Manage MLflow for experiment tracking, model registry and reproducible deployments.
• Deploy, operate and optimize ML workloads on AWS focusing on performance and cost.
• Develop scalable feature pipelines and feature stores, with scalable Scala-based ETL where applicable.
• Build monitoring, alerting and observability for production models and data drift.
• Collaborate with Data Scientists to productionize models and improve constraints.
• Perform post-deployment analyses to evaluate model performance and reliability.
• Contribute to platform improvements, automation and MLOps best practices.
• Mentor fellow engineers and foster a strong engineering culture.

Connaissances

ML engineering

MLOps

Databricks

MLflow

AWS

Scala

Spark

Docker

Kubernetes

CI/CD

Monitoring

Software engineering

Communication

Outils

Databricks

MLflow

AWS

Scala

Docker

Kubernetes

Spark

JVM

Description du poste

Eneco is building reliable, production‑grade machine learning systems within the Energy Management Systems domain in Rotterdam. The role focuses on delivering scalable ML pipelines, MLOps tooling and platform improvements across Databricks, MLflow and AWS.

You will work with Data Scientists, Data Engineers and Software Engineers to productionize models, monitor performance and continuously improve deployed solutions, while mentoring peers and contributing to a culture of collaboration and