2025 Summer Internship Program
Location:
This role is scheduled to be 100% remote. While remote, finalists MUST reside in one of the following states to be eligible for employment with Kaiser Permanente: CA, OR, WA, HI, CO, GA, MD, VA, CT, DC, or IL.
Department Description:
We harness cutting-edge ML/AI and advanced analytics to transform how patients, providers, and employees access information across our healthcare ecosystem. By developing intelligent search experiences and data-driven insights, our team streamlines workflows, enhances collaboration, and improves health outcomes.
Intern Project(s):
During this internship, you’ll be helping build our AI-driven search platform. Responsibilities include:
1) Search Pipeline: Collaborate on designing and implementing a scalable data ingestion and indexing process, creating the groundwork for advanced AI-based retrieval methods.
2) AI Model Development: Research and prototype ML/AI algorithms to transition from basic keyword search to intelligent, context-aware query handling.
3) Performance Optimization & Metrics: Evaluate and improve model precision/recall, while setting up robust A/B testing frameworks to guide data-driven enhancements.
4) Deployment & Integration: Work with cross-functional teams to integrate your solutions into production, ensuring reliability, scalability, and compliance with Kaiser Permanente’s privacy and security standards.
By the end of the internship, you will have shaped the next generation of our search capabilities delivering measurable impact and setting a solid AI foundation for future innovation.
Target Majors:
Computer Science; Math/Statistics; Data Science
Target Skills:
ML & NLP: Proficiency in Python-based ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and natural language processing techniques.
Data Wrangling: Experience gathering, cleaning, and transforming large structured and unstructured datasets.
Search Algorithms & Retrieval: Familiarity with search technologies (e.g., Elasticsearch, Lucene) or recommendation systems.
Cloud & MLOps: Understanding of cloud platforms (AWS, GCP, or Azure) and best practices for model deployment, monitoring, and CI/CD.
Software Engineering: Strong coding skills, version control (Git), and the ability to write clean, maintainable code.
Analytical & Problem-Solving: Comfortable working with performance metrics, debugging, and iterative experimentation.
Job Summary:
