About the job
Make a Meaningful Impact
As an Applied Machine Learning Engineer at Strata, you will be at the forefront of innovation, collaborating with architects, data scientists, AI developers, platform engineers, and product teams to integrate cutting-edge AI and ML capabilities into our healthcare platform. Your contributions will be pivotal in driving advancements in generative AI and beyond, as you employ a diverse array of machine learning techniques to tackle complex healthcare challenges. By developing next-generation AI agents, algorithms, and computational engines, you will play a crucial role in enhancing Strata's market leadership, streamlining operational efficiency, and empowering healthcare providers to deliver top-notch care while ensuring financial sustainability.
A Day in Your Role
Transform the latest research (e.g., arXiv papers) into practical, production-ready solutions using Python.
Prototype and refine machine learning models, focusing on regression, causal inference, optimization, and vector embeddings.
Work collaboratively with cross-functional teams to seamlessly embed ML and AI functionalities into our software platform.
Teaming up with data scientists, you will design experiments and apply statistical methods to analyze real-world data.
Optimize, test, and scale ML models to support essential healthcare analytics.
Our Technology Ecosystem
Our core platform serves over half of the nation's leading healthcare providers, enabling them to harness financial, operational, and clinical data effectively. Our AI and ML technology stack encompasses:
Programming Languages & Libraries: Python, PyTorch, NumPy, Pandas, Polars, PyMC
Infrastructure: AWS, Snowflake, Docker, GitHub
Techniques & Tools:
Regression (both Bayesian and non-Bayesian)
Vector embeddings, similarity analysis, clustering techniques
Core statistics and distributions for exploratory data analysis (EDA)
Optimization strategies (multi-armed bandit, mixed integer programming)
Causal inference and probabilistic modeling

