Canals - ML/AI Engineer
Tasks
- Build machine learning models for operational use cases
- Deploy monitoring and iterate in production
- Design build deploy AI powered product features
- Develop and maintain LLM powered systems
- Establish best practices for prompt engineering model evaluation observability and cost optimization
- Improve scalability reliability and performance of AI infrastructure
- Integrate AI systems into product workflows
- Own full lifecycle of ML systems
Perks/Benefits
Skills/Tech-stack
API Design | Anomaly Detection | Anthropic API | Cloud infrastructure | Distributed Systems | Document Classification | Forecasting | Inference Systems | Langchain | Language Models | Large Language Models | Llamaindex | Model Evaluation | Observability | OpenAI API | Prompt engineering | PyTorch | Python | RAG | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer | ML Engineer
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