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Responsibilities
- Design, develop, and deploy machine learning models for real-world business use cases
- Preprocess and analyze large datasets to extract actionable insights
- Collaborate with data scientists, engineers, and stakeholders to define ML project scope and objectives
- Optimize model performance and ensure scalability in production environments
- Maintain clear documentation and communicate findings to both technical and non-technical audiences
- Monitor and troubleshoot model performance post-deployment
- Stay up-to-date with latest ML tools, trends, and best practices
Requirements
- Proven experience as a Machine Learning Engineer or similar role
- Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, etc.
- Hands-on experience with data pipelines, model training, evaluation, and deployment
- Solid understanding of statistics, data structures, and algorithms
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and containerization tools (Docker, Kubernetes)
- Experience with MLOps tools is a plus (e.g., MLflow, DVC, Airflow)
- Ability to work independently and manage time effectively in a hybrid work setting
- Fluent in English; French or Dutch is a plus
Nice to Have
- Experience with NLP, computer vision, or time series forecasting
- Background in data engineering or software development
- Previous work in finance, healthcare, or logistics sectors
Key Skills
Ranked by relevance
machine learning
containerization
data structures
computer vision
tensorflow
pytorch
python
docker
mlflow
cloud
mlops
aws
gcp
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- Posted
- Jun 06, 2025
- Type
- Contract
- Level
- Mid-Senior
- Location
- Brussels Metropolitan Area
- Company
- Parallel Consulting
Industries
IT Services
IT Consulting
Categories
Other
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