Strata Decision Technology, LLC in
Applied Machine Learning Engineer
Strata Decision Technology, LLC in, Chicago, Illinois, United States, 60290
How You’ll Make an Impact As an Applied Machine Learning Engineer, you will collaborate with architects, data scientists, agentic AI developers, platform engineers, and the product team to build advanced AI and ML capabilities into our platform. Your work will drive innovation in generative AI and beyond, integrating and customizing a wide range of machine learning techniques to solve complex problems in healthcare. By developing next-generation AI agents, algorithms, and computation engines, you will help Strata strengthen its market leadership, improve operational efficiency, and support healthcare providers in delivering high-quality care while maintaining financial health.
Are you the right applicant for this opportunity Find out by reading through the role overview below. A Day in the Life 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. Our Technology Stack Our core platform is used by more than half of the nation’s leading healthcare providers, enabling them to leverage financial, operational, and clinical data. Our AI and ML stack includes: Infrastructure:
AWS, Snowflake, Docker, GitHub 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 What We’re Looking For We’re seeking a technically curious engineer who thrives on turning theory into practice. The ideal candidate has: Strong experience implementing ML models in Python. Familiarity with regression, embeddings, causal inference, and optimization techniques. Experience applying statistical methods to exploratory data analysis. Comfort working with modern ML libraries and frameworks. Bonus points if you have worked with: Graph algorithms. Claude Code, Docker, and GitHub. Salary and Benefits Estimated Salary Range:
$117,000-150,000 . Actual salary will be determined based on factors including, but not limited to, skill set and level of experience. Strata also provides discretionary variable pay programs based on role. In addition, Strata provides a comprehensive benefits package including retirement benefits, health and welfare benefits, paid time off, parental leave, life and accident insurance, and other voluntary and well-being benefits. How We Work The preferred location for this role is in Chicago, IL or St. Louis, MO. We value our people spending time together and have campuses hosting in-person events located in both cities. We are truly a hybrid environment with all team members experiencing the flexibility to work from home. Our Core Values We celebrate what makes each member of our team unique, and our core values guide how we approach our work and how we interact with customers. Our core values are: We connect with positive intent. We are helpful. We own it. We are humble.
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Are you the right applicant for this opportunity Find out by reading through the role overview below. A Day in the Life 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. Our Technology Stack Our core platform is used by more than half of the nation’s leading healthcare providers, enabling them to leverage financial, operational, and clinical data. Our AI and ML stack includes: Infrastructure:
AWS, Snowflake, Docker, GitHub 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 What We’re Looking For We’re seeking a technically curious engineer who thrives on turning theory into practice. The ideal candidate has: Strong experience implementing ML models in Python. Familiarity with regression, embeddings, causal inference, and optimization techniques. Experience applying statistical methods to exploratory data analysis. Comfort working with modern ML libraries and frameworks. Bonus points if you have worked with: Graph algorithms. Claude Code, Docker, and GitHub. Salary and Benefits Estimated Salary Range:
$117,000-150,000 . Actual salary will be determined based on factors including, but not limited to, skill set and level of experience. Strata also provides discretionary variable pay programs based on role. In addition, Strata provides a comprehensive benefits package including retirement benefits, health and welfare benefits, paid time off, parental leave, life and accident insurance, and other voluntary and well-being benefits. How We Work The preferred location for this role is in Chicago, IL or St. Louis, MO. We value our people spending time together and have campuses hosting in-person events located in both cities. We are truly a hybrid environment with all team members experiencing the flexibility to work from home. Our Core Values We celebrate what makes each member of our team unique, and our core values guide how we approach our work and how we interact with customers. Our core values are: We connect with positive intent. We are helpful. We own it. We are humble.
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