ML Infrastructure Architect

Select appropriate algorithms and architectures based on data characteristics, performance requirements, and use-case complexity.

Conduct feature engineering, hyper parameter 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 teams.

Stay current with advancements in ML algorithms, generative architectures (e.g., transformers, graph neural networks), and tooling (e.g., MLflow, Kubeflow, Hugging Face) and so on.

JD At least 7 + years of experience, Strong in Gen AI, ML, Python, TypeScript. Palantir Foundry is an advantage Design and implement AI/ML models tailored to specific business problems (preferably Insurance), including generative LLM models and traditional ML approaches.