MLOps Engineer

Findmino; Amsterdam; On-site; EUR 60,000 - 90,000; Full time

Job summary

Likemymind Netherlands B.V. is seeking an MLOps Engineer to bridge data science and production by deploying, monitoring, and maintaining machine learning models in production. You will develop CI/CD pipelines for ML workflows, manage feature stores, and ensure model reliability with DevOps collaboration.

You will work with data scientists to productionize models and continuously monitor performance, detect drift, and implement automated retraining pipelines to uphold quality and compliance.

Qualifications

• Requires at least an HBO bachelor’s degree in computer science, data science, software engineering, or a comparable technical field.
• A WO master’s degree can be an advantage, but practical ML deployment and DevOps tool experience often compensates.
• Strong interest in ML deployment, data pipelines, and production infrastructure is essential.

Responsibilities

• Build and maintain CI/CD pipelines for ML workflows.
• Deploy, monitor, and maintain ML models in production environments.
• Collaborate with data scientists and DevOps to optimize infrastructure and model quality.

Skills

CI/CD for ML

ML deployment

Monitoring dashboards

Data pipelines

Cloud computing

Education

HBO Bachelor in CS/Data Science/Software Engineering

WO Master’s degree (advantage)

Tools

Docker

Kubernetes

DevOps tooling

Job description

(MLOps Engineer) As an MLOps Engineer, you build the bridge between data science and production environments by deploying, monitoring, and maintaining machine learning models. You develop CI/CD pipelines specifically for ML workflows, manage feature stores, and ensure that models perform reliably in production. You work closely with data scientists to make their models production-ready and with DevOps teams to optimize infrastructure. Additionally, you continuously monitor model performance, detect model drift, and implement automated retraining pipelines to ensure quality.

Required Education

For this position, you need at least an HBO bachelor's degree in computer science, data science, software engineering, or a comparable technical field. The N&T specialization profile in secondary school provides the best preparation through its focus on mathematics, physics, and computer science. Subjects like programming, statistics, and cloud computing are essential. A WO master's degree can be an advantage, but extensive practical experience with ML deployment and DevOps tools often compensates for a lower educational level.

Required Skills

You often start as a Data Engineer or Software Engineer with an interest in machine learning, where you gain experience with data pipelines and deployment. You then grow into an MLOps Engineer role, where you specialize in ML-specific infrastructure. With more experience, you can advance to Senior MLOps Engineer or ML Platform Architect, where you design enterprise-wide ML platforms. Eventually, you can become Head of ML Engineering or specialize as an ML Infrastructure Consultant for various organizations.

AI Impact on the job

Paradoxically, as an MLOps Engineer, you actually benefit from the AI revolution because more ML models need to be brought into production. AI tools do help you automate routine deployment tasks and generate monitoring dashboards. Your work shifts toward more complex challenges such as multi-model orchestration, real-time inference optimization, and responsible AI deployment. The demand for your expertise grows exponentially as organizations realize their AI ambitions.

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