Participate in developing state-of-the-art ML solutions to address large-scale healthcare problems
Help develop pipelines that collect, preprocess, and deliver data with a measurable quality
Write production-ready software with well-tested and efficient algorithms
Develop state-of-the-art ML algorithms across computer vision, large-language models, and probabilistic inference to solve problems like medical document entity extraction, medical coding and claim outcome prediction
Own ML services end-to-end, including problem discovery, data pipeline development, inference optimizations, model experimentation, and service deployment
Help build novel, application-specific ML models - all of our products are built from the ground up with ML at their core, enabling us to deploy our predictions in new and interesting ways

Requirements

Master's degree in Computer Science or similar
5+ years of work experience in machine learning and data engineering
Have experience launching production systems from the ground up
Proficiency in one or more programming languages such as Python and C++
Development experience with cloud platforms such as Spark, AWS & k8s
Knowledge of ML frameworks such as Scikit-Learn, Pytorch & TensorFlow
Full-stack development experience for an end-to-end ML solution
Ideal experience with Large Language Models, including both open source model deployment and agentic workflows.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdata engineeringproduction systemsPythonC++cloud platformsSparkAWSk8sML frameworks

Certifications

Master's degree in Computer Science