Remote Generative AI Engineer Intern – Health Insurance Risk

Overview

KARELYTICS LLC is an AI-driven platform that transforms health insurance risk management by combining actuarial science, predictive analytics, and machine learning. The platform delivers real-time risk assessment, pricing optimization, and fraud detection for health insurance organizations and their partners. Its three core modules focus on smart risk assessment for accurate premium pricing, coverage optimization for personalized insurance plans, and AI-powered fraud detection enhanced with blockchain-based secure claims processing. KARELYTICS supports health insurance companies, healthcare providers, and policymakers in achieving financial sustainability, better policy decisions, and effective risk optimization, ultimately contributing to more affordable health insurance for consumers.

Role Description

The Generative AI Engineer internship is a remote role focused on researching, designing, and prototyping generative AI models for health insurance risk management and analytics. Day-to-day responsibilities include experimenting with large language models and other generative architectures, preparing and cleaning datasets, and building proof-of-concept applications and APIs that integrate with the Karelytics platform. The intern will collaborate with data scientists, actuaries, and software engineers to translate business needs into technical solutions, document experiments and findings, and help evaluate model performance, reliability, and fairness. This internship offers exposure to real-world insurance data, practical MLOps workflows, and product-focused AI development in a highly regulated domain.

Qualifications

• Strong foundation in programming for AI/ML development (e.g., Python, familiarity with libraries such as PyTorch or TensorFlow).
• Knowledge of machine learning and deep learning fundamentals, including experience or coursework involving generative models and large language models.
• Ability to work with data pipelines: data cleaning, preprocessing, feature engineering, and basic model evaluation techniques.
• Understanding of software engineering practices such as version control (Git), testing, and documentation for collaborative development.
• Interest in or exposure to healthcare, health insurance, actuarial science, or financial risk analytics is beneficial.
• Strong analytical, problem-solving, and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Ability to work independently in a remote environment, manage time effectively, and contribute to a distributed team.
• Currently pursuing or recently completed a degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience.