Description

You will design and implement AI/ML models, including generative LLMs and traditional ML approaches, tailored to business problems in the insurance domain.

This role is hybrid.

Responsibilities

• Design and implement AI/ML models using Python and TypeScript, including generative LLMs and traditional ML approaches.
• Conduct feature engineering, hyperparameter tuning, and model validation to optimize performance and generalizability.
• Evaluate model performance using statistical metrics and real-world testing to ensure robustness and fairness.
• Collaborate with cross-functional teams to integrate models into production environments.
• Monitor, maintain, and retrain models to ensure continued accuracy and compliance with ethical standards.

Required Skills

• At least 7 years of experience in data engineering or machine learning.
• Strong proficiency in Python and TypeScript.
• Experience with ML libraries such as TensorFlow, PyTorch, and scikit-learn.
• Knowledge of generative AI and LLM architectures.
• Ability to select appropriate algorithms and architectures based on data characteristics and use case complexity.
• Experience with model monitoring and retraining processes.
• Strong documentation skills for model development processes.

Preferred Skills

• Experience with Palantir Foundry and AIP Functions.
• Familiarity with ML tooling such as MLflow, Kubeflow, and Hugging Face.
• Background in the insurance industry.

Key Skills

Education

Any Graduate