AI Knowledge Data Engineer
Tasks
- Align knowledge architecture with business objectives
- Architect retrieval-augmented generation workflows
- Build scalable data pipelines
- Design LLM tool specifications
- Design cognitive memory systems
- Develop ontologies and knowledge graphs
- Evaluate and integrate LLM and retrieval technologies
- Fuse heterogeneous knowledge bases
- Implement knowledge retrieval strategies
- Maintain documentation of models and workflows
- Orchestrate training data operations
Perks/Benefits
- Competitive remuneration package
- Excellent office location and facilities
- Free bike parking and showers
- Gaming areas
- Great work-life balance
- Health and dental care
- Special discounts
- Team bonding events
Skills/Tech-stack
Airflow | Cloud Platforms | Data Curation | Data Lineage | Data Modeling | Data Processing | Data Versioning | Dense and sparse retrieval | Dense retrieval | Distributed data | Distributed data processing | Elasticsearch | Elasticsearch Vector | Elasticsearch Vector Search | Faiss | Information Retrieval | Knowledge Retrieval | Knowledge graph | Knowledge representation | Kubeflow | Language Models | Large Language Models | OWL | Ontology | PyTorch | Python | RDF | Ranking algorithms | Retrieval-Augmented Generation | SPARQL | Semantic data | Semantic data modeling | Spark | Sparse Retrieval | TensorFlow | Training data | Training data curation | Vector Search | Weaviate
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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