Sytac

Java and JavaScript software development consultancy

Senior MLOps Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeRotterdam, NetherlandsNo salary listedIn-person

About the Job

Requirements

The candidate must be available from January 5, 2026 to January 4, 2027, for 40 hours per week, with possible extension.
A completed Bachelor's or Master's degree is required.
Experience as a technical lead, capable of guiding and enabling a team, is required.
Experience designing and improving MLOps infrastructure within a large, complex organization is required.
At least 5 years of professional experience in machine learning product development within an MLOps context, from data preparation and model training through deployment and monitoring, is required.
Excellent Python skills and solid software design principles, including object-oriented programming and design patterns, are required.
Demonstrable experience building and maintaining an MLOps or data platform is required; Azure experience is ideal and Databricks experience is preferred.
Understanding how to deploy machine learning solutions reliably and securely at scale is required.
Knowledge of Terraform or infrastructure as code is required.

Responsibilities

Design, build, and improve MLOps infrastructure.
Develop and roll out the internal MLOps platform, including automated pipelines, model registration, and deployment workflows in Azure Databricks with MLflow for model management.
Enable data science models to be deployed to production more efficiently and reliably.
Ensure large-scale time-series forecasting workflows running on Databricks Jobs with MLflow and scheduled via Apache Airflow run smoothly.
Introduce CI/CD best practices for machine learning via Azure DevOps, supporting proper versioning of code, models, and data.
Transfer knowledge to and coach existing engineers so the team becomes more mature and self-sufficient and the improvements are sustained.

Desired Qualifications

Experience with the current technology stack is a plus, including Apache Spark, Azure Databricks, MLflow, Apache Airflow, Azure DevOps, and data lineage or versioning.

Senior MLOps Engineer

Profile

The energy transition is in full motion, and data plays an essential role in enabling it. Our client manages vast amounts of data and is experiencing rapid growth in the number of data science use cases. To fully support their data scientists, they are building a modern MLOps platform within Azure. A new MLOps environment (based on Azure Databricks) has recently been set up, and further expansion is underway. To strengthen their MLOps capability and support ongoing use cases, our client is seeking temporary reinforcement in the form of a Senior MLOps Engineer.

In this role, you will bring your expertise to design, build, and improve the MLOps infrastructure. Your initial focus will be on developing and rolling out the internal MLOps platform: setting up automated pipelines, model registration, and deployment workflows in Azure Databricks, including the use of MLflow for model management. You will ensure that data science models can be deployed to production more efficiently and reliably. Examples include large-scale time-series forecasting workflows running on Databricks Jobs with MLflow, scheduled via Apache Airflow; you ensure that these pipelines run smoothly. You will also introduce structure and best practices for CI/CD in machine learning (via Azure DevOps) to ensure proper versioning of code, models, and data.

As the assignment progresses, your focus will shift toward knowledge transfer and coaching the existing engineers. You help the team grow, mature, and become self-sufficient, ensuring that the improvements you introduce are embedded for the long term. You leave the team stronger than you found it.

Requirements

Candidate is available from 05/01/2026 to 04/01/2027 for 40 hours per week, with possible extension
Completed HBO/WO (Bachelor's/Master's) degree
Experience as a tech lead, capable of guiding and enabling a team
Experience designing and improving MLOps infrastructure within a large, complex organization
At least 5 years of professional experience in machine learning product development within an MLOps context from data preparation and model training to deployment and monitoring
Excellent Python skills and solid software design principles (OOP, design patterns)
Demonstrable experience building and maintaining an MLOps or data platform, ideally in Azure, and preferably with Databricks
Understanding of what it takes to deploy ML solutions at scale reliably and securely
Knowledge of Terraform or Infrastructure-as-Code
Experience with the current tech stack is a plus: Apache Spark, Azure Databricks, MLflow, Apache Airflow, Azure DevOps, data lineage / versioning

About Sytac:

At Sytac, we’re on a mission to become the leading name in digital solutions. We aim to help Dutch companies stay ahead with the latest technology. We’re not just another IT company; we’re a lively team of tech enthusiasts dedicated to pushing the boundaries of what’s possible. Our success comes from our amazing team—people who love technology and are dedicated to being the best in everything we do.

Our goal is to be recognized as one of the top 10 tech partners and one of the top 25 employers for tech professionals. Join us as we work to make a real difference in the world of technology!

If you’re excited about leveraging your AI expertise to drive innovation and make a real impact, we’d love to hear from you!

+31624547808 [email protected]

Deadline: 10th of December at 17:00

About the Company

Sytac

Java and JavaScript software development consultancy

Sytac provides access to top JVM and JavaScript developers who work with clients to build complex software applications. Its core offering is assembling and guiding skilled development teams that are aligned to the client’s technical needs and project goals. The product works by matching and deploying consultants with the right expertise, maintaining a developer-first culture, and supporting ongoing knowledge sharing through monthly sessions to keep engineers up to date. What sets Sytac apart is its explicit focus on developer quality and continuous learning—not just staff augmentation—with a steady emphasis on maintaining skill relevance and delivering hands-on coding excellence within the Netherlands. The company’s goal is to help organizations ship sophisticated software faster by providing highly capable, continuously educated engineering talent that stays in sync with current technologies.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: Haarlem, Netherlands
Founded: 2005

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