Applied Machine Learning Engineer

Read and translate the latest research (e.g., arXiv papers) into production-ready solutions in Python.

Prototype and iterate on machine learning models, focusing on areas such as regression, causal inference, optimization, and vector embeddings.

Collaborate with cross-functional teams to embed ML and AI capabilities directly into our software platform.

Partner with data scientists to design experiments and apply statistical concepts to real-world data.

Optimize, test, and scale ML models to support mission-critical healthcare analytics.

Regression (with and without Bayesian priors)

Vector embeddings, similarity, clustering

Core statistics and distributions for EDA

Optimization methods (multi-armed bandit, mixed integer programming)

Causal inference and probabilistic modeling