Sr. GenAI Engineer
Tasks
- Build agentic frameworks for capital markets applications
- Create embeddings and information extraction pipelines
- Deploy machine learning models and monitor performance
- Design and develop machine learning architectures
- Develop zero shot learning and few shot learning solutions
- Implement Retrieval-Augmented Generation (RAG) systems
- Integrate generative AI tools into existing systems
- Lead experimentation model evaluation and fine tuning
- Provide code reviews and best practices
- Stay updated on deep learning NLP and AI methodologies
Perks/Benefits
- Comprehensive insurance
- Higher education certification policy
- Hybrid work policy
- Learning and development support
- On demand course access
- Paid annual leave
- Paid coaching opportunities
- Personal leave
- RRSP match
- Udemy for Business access
Skills/Tech-stack
Agentic Frameworks | Deep learning | Distributed Computing | Embeddings | Few-Shot Learning | Few-shot | Fine Tuning | Generative AI | Information Extraction | Language Processing | MLOps | Machine Learning | Model Deployment | Model Fine-tuning | Model Monitoring | Natural Language | Natural Language Processing | Neural Networks | Rerankers | Retrieval-Augmented Generation | Zero-Shot | Zero-shot Learning
Education
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