IT Recruitment – MLOps
MLOps Engineers ensure that machine learning models run reliably, scalably and manageably in production. Without MLOps, most AI projects fail before they deliver business value.
As more and more organizations are actually operationalizing AI, the demand for experienced MLOps Engineers is growing rapidly. Iduet supports organizations in finding MLOps specialists for permanent positions, interim assignments and AI operationalization projects.
25+
years of experience
MLOps
specialization
Interim
& fixed roles
Scarcity & demand
MLOps is a relatively young field that requires a rare combination: deep knowledge of both machine learning and cloud infrastructure, DevOps principles and software engineering. Candidates with manufacturing MLOps experience are therefore hard to find and are actively approached by multiple employers at once.
Iduet selects MLOps Engineers on more than tooling knowledge alone.
Responsibilities
MLOps Engineers operate at the intersection of machine learning, DevOps and data engineering – making the difference between AI as an experiment and AI as a mission-critical application.
🚀
Scalable and reproducible deployment of ML models to production.
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Automated pipelines for training, testing and model releases.
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Monitor model performance, data drift and operational stability.
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Centralized storage and management of features for training and inference.
⚙️
Orchestration of end-to-end ML workflows with Airflow or Kubeflow.
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Ensuring reproducibility, audit trails and responsible AI use.
Our approach
We combine over 25 years of IT recruitment experience with specialized knowledge of the ML Engineering and MLOps landscape. As a result, we select MLOps Engineers not only on tooling knowledge, but also on their ability to structurally and scalably implement AI operationalization within an organization.
How we select
Frequently Asked Questions
An MLOps Engineer automates and manages the full lifecycle of machine learning models: from training and validation to deployment, monitoring and retraining in production. They combine DevOps principles with ML knowledge to keep AI solutions reliable and scalable.
Without MLOps, most AI projects get stranded before they deliver real business value. Models degrade in production, pipelines are not reproducible, and teams lack insight into model performance. MLOps is the crucial link between AI experimentation and structural business impact.
An ML Engineer focuses primarily on building and optimizing models. An MLOps Engineer focuses on the operational side: deployment, monitoring, pipelines and infrastructure. In practice, the roles overlap, but MLOps Engineers typically have a stronger DevOps and infrastructure background.
The most requested stack includes Kubernetes, Docker, MLflow, Kubeflow, Airflow and cloud platforms such as Azure ML, AWS SageMaker or Google Vertex AI. In addition, knowledge of Terraform, CI/CD tooling and monitoring solutions such as Prometheus and Grafana is valuable.
Yes Iduet mediates both permanent and interim MLOps Engineers. For organizations looking to rapidly operationalize production AI or strengthen a temporary MLOps team, we can often provide a suitable profile quickly.
Depending on the specificity of the profile, we can often present an initial shortlist within 7-14 working days. This is regularly faster for interim assignments, as we maintain an active network of available MLOps specialists.
IT Specializations
Getting Started
Iduet will find you the MLOps Engineer who combines technical infrastructure knowledge with ML expertise – from junior MLOps Engineer and pipeline specialist to senior ML Platform Engineer and interim AI operations specialist.
Iduet for temporary and permanent ICT professionals in the fields of AI and Data, IT management, IT security and IT interim.
Specializations:
ICT recruitment
Cloud recruitment
Data & AI recruitment
IT management
IT Interim
We are part of Iduet Group B.V., consisting of:
Finhire.nl – Fintech – Finance positions
Gridmasters.nl – Sustainable energy
Tomorrowsleaders.nl – Sales & marketing