MLOps Engineer – Data Analytics Platform
Core
Building and managing scalable ML batch processing pipelines, ETL workflows, and model lifecycle management on Google Cloud Platform.
Role type
Senior MLOps Engineer (Data Analytics Platform)
Builds
Cloud-native ML batch processing platform, automated data pipelines, and model deployment infrastructure for ING's data ecosystem.
Domain
Financial services, Cloud-native Data Engineering, Machine Learning Operations
Deliverable
production ML models | infrastructure
Required skills
Apache Airflow workflow orchestration, MLflow lifecycle management, Google Cloud Platform (GCP) services, Docker containerization, CI/CD pipelines, ETL process design, ML pipeline monitoring and troubleshooting, cloud-native architecture design, distributed data processing concepts.
Preferred skills
Airflow-based workflow optimization, Vertex AI integration, Spark distributed batch processing, Kedro pipeline frameworks, Kubernetes management.
Technologies
Apache Airflow, MLflow, Google Cloud Platform (BigQuery, Vertex AI, Cloud Storage), Docker, Kubernetes, Spark, CI/CD tools.
Responsibilities
Developing and managing workflow orchestration using Airflow, supporting model lifecycle management using MLflow, migrating ML Batch platform from on-premise to GCP, refactoring ML pipelines for cloud-native environments, developing templates for productionizing ML solutions, integrating ML pipelines with CI/CD, ensuring scalability and reliability of ML workloads, troubleshooting and optimizing pipeline performance, participating in on-call support, collaborating with stakeholders on scalable solutions.
Seniority
Senior, hands-on IC