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BrusselsHybrid40 hours/week<3months
This position can be filled with either a permanent contract or a freelance contract. You will work for an organization in the Brussels region.
What you do
- Develop, implement, and manage machine learning solutions within cloud and on-premise environments.
- Deploy machine learning models, with a specific focus on Amazon SageMaker.
- Monitor and maintain the performance, availability, and scalability of models in production.
- Implement best practices for version control, model tracking, and end-to-end model lifecycle management.
- Design and manage scalable, reliable, and secure infrastructure for machine learning projects.
- Ensure seamless integration between various infrastructure and data components.
- Set up, implement, and maintain CI/CD pipelines for ML and data solutions.
- Apply Infrastructure as Code (IaC) to make infrastructure consistent, reproducible, and manageable.
- Collaborate with data scientists, data engineers, product owners, architects, and business stakeholders to understand requirements and realize appropriate technical solutions.
- Perform technical and business analyses and translate needs into concrete ML and data solutions.
- Perform data analyses in Python, including with Jupyter Notebooks.
- Contribute to data engineering workflows and work with tools such as dbt and/or Dagster.
- Monitor new developments in machine learning, cloud, DevOps, and MLOps and translate them into concrete improvements.
- Optimize existing workflows and systems, with attention to performance, reliability, and FinOps.
- Participate in incident response and root cause analysis for issues related to data integrity, availability, performance, and data quality.
- Troubleshoot and resolve technical and data-related problems within production environments.
- Support business intelligence and analytics by developing dashboards and reports.
- Contribute to further professionalization of MLOps, data engineering, and cloud-based analytics within the organization.
Profile
- Bachelor's or Master's degree in Computer Science, Informatics, Information Technology, or a comparable field.
- Demonstrable experience as a Machine Learning Engineer, MLOps Engineer, or in a similar role.
- Strong experience with machine learning operations (MLOps) and model lifecycle management.
- Strong knowledge of Python and experience with data analysis via Jupyter Notebooks.
- Hands-on experience with both cloud and on-premise infrastructure.
- Experience with designing and managing infrastructure for machine learning and data solutions.
- Experience with DevOps principles and CI/CD pipelines.
- Experience with container technologies such as Docker.
- Experience with container orchestration, for example Kubernetes or Amazon ECS.
- Experience with Infrastructure as Code (IaC).
- Knowledge of Amazon SageMaker and AWS services is a strong plus.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
- Knowledge of data engineering and experience with dbt and/or Dagster.
- Knowledge of big data technologies such as Apache Spark and Kafka.
- Good knowledge of SQL and experience with SQL and NoSQL databases.
- Experience with building dashboards in Power BI and/or QlikView.
- Knowledge of additional programming languages such as R, Java, or C++ is a plus.
- Experience with business and technical analyses.
- Strong problem-solving and analytical skills and the ability to think critically and creatively.
- Strong communication and collaboration skills.
- Ability to work independently and efficiently manage multiple tasks and priorities.
- Proactive attitude and a strong focus on continuous improvement.
- Very good knowledge of Dutch.
- Passive knowledge of French.
How to apply
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