Principal Data and Applied Scientist
Montreal, Quebec, CA, H3B 0B3
CAD 140K-202K (estimate) Senior-level Full Time
Tasks
- Apply machine learning and deep learning
- Build generative AI and LLM solutions
- Build semantic models for AI agents
- Collaborate cross functionally to translate business needs into AI solutions
- Create embeddings and vector databases
- Deploy and operate AI and ML solutions in production
- Design and maintain enterprise ontologies
- Develop RAG pipelines
- Develop knowledge graph based solutions
- Evaluate AI solutions on enterprise datasets
- Implement semantic retrieval and knowledge grounding
- Integrate AI workflows across cloud data platforms
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS S3 | Azure | Azure Data | Azure Data Lake | Azure Data Lake Storage | Business Process | Business Process Intelligence | Cloud platform | Cypher | Data Lake Storage | Databricks | Deep learning | Embeddings | Generative AI | Google BigQuery | Google Cloud | Google Cloud Platform | Graph Databases | HANA Cloud | Knowledge graphs | Language Models | Large Language Models | Machine Learning | OWL | Process Intelligence | Property Graph | Property Graph Databases | PyTorch | Python | RDF | RDF RDFS | RDF triple stores | Retrieval-Augmented Generation | SAP Datasphere | SAP HANA | SAP HANA Cloud | SKOS | SPARQL | SQL | Scikit-learn | Semantic Retrieval | Shacl | Statistical modeling | TensorFlow | Triple-Stores | Vector Database
Education
Roles
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