Develops modular probabilistic models and algorithms for Bayesian statistical inference and machine learning in Julia, focusing on backend implementation, scaling statistical procedures, and integrating into large software systems for finance and research applications.
Builds program synthesis pipeline for modular probabilistic models in finance and research applications. Requires experience with complex algorithms like graph theory and compilers, plus collaborative software engineering practices.
Develops modular probabilistic models and algorithms for Bayesian statistical inference and machine learning in Julia, focusing on backend implementation, scaling statistical procedures, and integrating into large software systems for finance and research applications.
Builds program synthesis pipeline for modular probabilistic models in finance and research applications. Requires experience with complex algorithms like graph theory and compilers, plus collaborative software engineering practices.