Machine Learning Operations (MLOps) Engineer

Placements24; Netherlands; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Hybrid work

Health, dental, and vision coverage

Continuous learning

Modern tooling

Retirement fund with matching

Job summary

Placements24 is seeking a highly skilled MLOps Engineer to bridge ML model development and production deployment in the Netherlands. You will design, implement, and manage the infrastructure, tools, and processes required to reliably build, train, test, deploy, and monitor ML models at scale.

This role collaborates with data scientists and software engineers to optimize model performance and lifecycle management in a forward‑thinking, hybrid environment that supports learning and growth.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in DevOps, SRE, or MLOps, with a focus on ML systems.
• Strong scripting in Python and Bash; Docker and Kubernetes experience.
• Experience with cloud ML services.
• Familiarity with ML workflows, model training, and deployment strategies.
• Understanding of software development best practices, including version control and automated testing.

Responsibilities

• Develop and maintain CI/CD pipelines for machine learning models, automating deployment and retraining processes.
• Implement robust monitoring and alerting systems for ML models in production, tracking performance, drift, and anomalies.
• Manage and scale ML infrastructure on cloud platforms (e.g., AWS SageMaker, Azure ML, GCP AI Platform).
• Collaborate with data scientists and software engineers to optimize model performance and ensure smooth integration.
• Develop and manage model versioning, experiment tracking, and artifact management systems.
• Implement best practices for MLOps to ensure reproducibility, scalability, and reliability of ML solutions.

Skills

MLOps

DevOps

SRE

Python

Bash

Docker

Kubernetes

Cloud ML

Education

Bachelor's degree in CS/Engineering

Tools

AWS SageMaker

Azure ML

GCP AI Platform

Job description

About the Role

Our client is seeking a highly skilled Machine Learning Operations (MLOps) Engineer to bridge the gap between machine learning model development and production deployment in Welkom . You will be responsible for designing, implementing, and managing the infrastructure, tools, and processes required to reliably build, train, test, deploy, and monitor ML models at scale. This role is crucial for ensuring the seamless integration of AI solutions into business operations and optimizing their performance and lifecycle management. Join a forward-thinking team focused on operationalizing AI for maximum impact.

Key Responsibilities

• Develop and maintain CI/CD pipelines for machine learning models, automating the deployment and retraining processes.
• Implement robust monitoring and alerting systems for ML models in production, tracking performance, drift, and anomalies.
• Manage and scale ML infrastructure on cloud platforms (e.g., AWS SageMaker, Azure ML, GCP AI Platform).
• Collaborate with data scientists and software engineers to optimize model performance and ensure smooth integration.
• Develop and manage model versioning, experiment tracking, and artifact management systems.
• Implement best practices for MLOps to ensure reproducibility, scalability, and reliability of ML solutions.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 3+ years of experience in DevOps, SRE, or MLOps, with a focus on ML systems.
• Strong proficiency in scripting languages (Python, Bash) and containerization technologies (Docker, Kubernetes).
• Experience with cloud platforms and their ML services.
• Familiarity with ML workflows, model training, and deployment strategies.
• Understanding of software development best practices, including version control and automated testing.

Benefits

• Competitive annual salary and performance incentives.
• Hybrid work arrangement providing flexibility for employees in Welkom .
• Comprehensive health, dental, and vision coverage.
• Opportunities for continuous learning and professional development in MLOps.
• Access to modern tooling and collaborative team environment.
• Retirement fund with matching contributions.