About the Role
Job Description
- Design and implement AI/ML models tailored to specific business problems (preferably Insurance), including generative LLM models and traditional ML approaches.
- Select appropriate algorithms and architectures based on data characteristics, performance requirements, and use-case complexity.
- Conduct feature engineering, hyperparameter tuning, and model validation to optimize performance and generalizability.
- Strong proficiency in Python, TypeScript and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Evaluate model performance using statistical metrics and real-world testing, ensuring robustness and fairness.
- Collaborate with cross-functional teams (business, product managers) to integrate models into production environments.
- Monitor, maintain, and retrain models to ensure continued accuracy, relevance, and compliance with ethical standards.
- Document model development processes for reproducibility and knowledge sharing across ...
- Design and implement AI/ML models tailored to specific business problems (preferably Insurance), including generative LLM models and traditional ML approaches.
- Select appropriate algorithms and architectures based on data characteristics, performance requirements, and use-case complexity.
- Conduct feature engineering, hyperparameter tuning, and model validation to optimize performance and generalizability.
- Strong proficiency in Python, TypeScript and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Evaluate model performance using statistical metrics and real-world testing, ensuring robustness and fairness.
- Collaborate with cross-functional teams (business, product managers) to integrate models into production environments.
- Monitor, maintain, and retrain models to ensure continued accuracy, relevance, and compliance with ethical standards.
- Document model development processes for reproducibility and knowledge sharing across ...
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