Principal Machine Learning Engineer
Toronto, ON, Canada
R
CAD 215K-230K Senior-level Full Time Found 1d ago
Tasks
- Architect and build production AI systems
- Bridge classical data science with generative AI
- Build customer relationships
- Collaborate on platform integration
- Define ai strategy
- Deliver measurable AI solutions
- Design evaluation frameworks
- Drive build-vs-buy decisions
- Establish architectural standards
- Identify high-impact AI opportunities
- Influence engineering standards
- Mentor data science team
- Own AI system quality
- Present to stakeholders
- Promote AI-native development practices
- Translate business needs into technical solutions
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | AI Programming | AI architecture | AI augmentation | AI integration | AI programming assistants | AI tools | AI workflows | AWS | Agent Frameworks | B testing | Classification | Claude Code | Cloud Platforms | Cursor | Data Engineering | Data Quality | Data Science | Distributed Systems | Embeddings | Engineering Fundamentals | Entity Extraction | Experimental Design | Feature Engineering | Feature Stores | Fine Tuning | GitHub Copilot | Information Retrieval | Langchain | Large-scale Datasets | Llamaindex | ML models | MLOps | Machine Learning | Model Deployment | Monitoring | NLP | Pipeline Design | Production Deployment | Prompt engineering | Python | RAG Architectures | SQL | Semantic similarity | Software Engineering | Software engineering fundamentals | Statistical Methods | Technical leadership | Text Analytics | Training models | Transformers | Vector Databases
Education
Bachelor's | Master's | PhD
Language: en |
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Clicks: 0
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