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🧠 Key Responsibilities
- Develop, train, and evaluate deep neural networks for tasks such as [e.g., image recognition, NLP, speech, time-series forecasting].
- Optimize models for performance, accuracy, and deployment constraints (e.g., latency, memory, throughput).
- Implement model training pipelines using frameworks such as PyTorch or TensorFlow.
- Collaborate with data engineers and domain experts to prepare and preprocess large-scale datasets.
- Contribute to model deployment using tools like ONNX, TensorRT, or cloud-native solutions (AWS, Azure, GCP).
- Stay up-to-date with the latest advancements in deep learning research and techniques.
🧰 Required Skills & Experience
- MSc/PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- 3+ years of hands-on experience in deep learning.
- Proficient in Python and deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
- Solid understanding of neural network architectures (CNNs, RNNs, Transformers, GANs, etc.).
- Experience with data pipeline tools (e.g., Pandas, Dask, Airflow) and model versioning (MLflow, Weights & Biases).
- Strong knowledge of software engineering practices: Git, Docker, CI/CD.
- Comfortable working in a Linux-based environment.
✅ Nice to Have
- Experience with edge AI or model quantization/pruning.
- Knowledge of MLOps principles and deployment on Kubernetes.
- Familiarity with regulatory or ethical aspects of AI in Europe (e.g., GDPR, AI Act).
- Previous experience in a freelance/consulting capacity in Belgium.
Key Skills
Ranked by relevance
ai
deep learning
pytorch
artificial intelligence
machine learning
neural networks
tensorflow
python
docker
pandas
mlflow
linux
cloud
mlops
gdpr
git
aws
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- Posted
- Jul 03, 2025
- Type
- Contract
- Level
- Mid-Senior
- Location
- Brussels Metropolitan Area
- Company
- Parallel Consulting
Industries
IT Services
IT Consulting
Categories
Other
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