Job Description:
">
This role involves working with machine learning models to drive business outcomes.
">
">
* The ideal candidate will have experience in designing, developing, and deploying machine learning models for real-world use cases.
">
* They will be responsible for preprocessing and analyzing large datasets to extract actionable insights.
">
* Collaboration with data scientists, engineers, and stakeholders is essential to define project scope and objectives.
">
* The ability to optimize model performance and ensure scalability in production environments is crucial.
">
* Maintaining clear documentation and communicating findings to both technical and non-technical audiences is key to success.
">
* Monitoring and troubleshooting model performance post-deployment is also an important responsibility.
">
">
Requirements:
">
">
* A proven track record as a Machine Learning Engineer or similar role.
">
* Strong proficiency in Python and popular machine learning libraries such as scikit-learn, TensorFlow, PyTorch, and XGBoost.
">
* A solid understanding of statistics, data structures, and algorithms.
">
* Familiarity with cloud platforms such as AWS, GCP, and Azure, as well as containerization tools like Docker and Kubernetes.
">
* Experience with MLOps tools is a plus, including MLflow, DVC, and Airflow.
">
* The ability to work independently and manage time effectively in a hybrid work setting.
">
* Fluency in English; French or Dutch is a plus.
">
">
Nice to Have:
">
">
* Experience with natural language processing, computer vision, or time series forecasting.
">
* A background in data engineering or software development.
">
* Previous work in finance, healthcare, or logistics sectors.
">