MIDDLE AI Architect & Data Science
Tasks
- Create technical knowledge base document patterns solutions and lessons learned
- Define and document generative AI architectural patterns RAG and vector search
- Design AI machine learning and data science architectures
- Design lakehouse and data mesh data architectures
- Develop machine learning deep learning and NLP models
- Evaluate AI ML development and deployment technologies frameworks and platforms
- Implement MLOps practices model drift monitoring A B testing and retraining
- Integrate LLMs and AI agents into business pipelines
- Perform exploratory data analysis feature engineering and model selection
- Produce technical specifications for reproducibility versioning and model quality
- Validate model correctness robustness and quality
Perks/Benefits
- Continuous learning training
- Meal vouchers
- Smart working up to 10 days per month
- Travel as needed
- Welfare benefits
Skills/Tech-stack
Apache Spark | Azure | CI/CD | Data Governance | Data Quality | Data mesh | Databricks | Deep learning | Delta Lake | Generative AI | Hugging Face | LLM | Lakehouse | Language Processing | MLOps | MLflow | Machine Learning | Natural Language | Natural Language Processing | PySpark | PyTorch | Python | RAG | SQL | Scikit-learn | TensorFlow | Unity Catalog | Vector Search
Education
Roles
AI | AI Architect | Architect | Data Scientist | Scientist
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