AI/ML Intern - Generative AI & Intelligent Systems

Ensora Health•Remote - Florida, FL

23h•Onsite

About The Position

Ensora Health is seeking a motivated AI/ML Intern to join their technology team. This 10-week, full-time summer internship focuses on cutting-edge projects involving Generative AI, AI agents, document analysis, and Retrieval-Augmented Generation (RAG) systems. The intern will gain hands-on experience building prototypes, exploring emerging technologies, and contributing to real-world AI solutions that support mental health care technology and customers.

Requirements

Currently pursuing a degree in Computer Science, Data Science, Artificial Intelligence / Machine Learning, Software Engineering, Statistics, Applied Mathematics, Health Informatics, or a related field (or equivalent practical experience).
Juniors and Seniors preferred.
Proficiency in Python and familiarity with common ML/DL frameworks (e.g., PyTorch, TensorFlow).
Basic understanding of LLMs and NLP concepts (tokenization, embeddings, prompts, evaluation).
Working knowledge of SQL and data handling (ideally PostgreSQL or similar).
Strong curiosity about AI/ML and enthusiasm for experimenting with new tools and techniques.
Comfort working with data, running experiments, and iterating based on results.
Ability to document work clearly, collaborate with others, and ask thoughtful questions.
Interest in healthcare data workflows and learning about compliance considerations (e.g., HIPAA).

Nice To Haves

Exposure to LangChain, LlamaIndex, or other AI orchestration frameworks.
Experience with vector databases and RAG patterns.
Familiarity with cloud AI services such as Azure OpenAI, AWS Bedrock, or GCP Vertex AI.

Responsibilities

Investigate state-of-the-art techniques in large language models (LLMs), AI agents, and orchestration frameworks such as LangChain and LlamaIndex.
Assist in designing and building proof-of-concept models for AI-driven workflows, document analysis, and knowledge retrieval systems.
Clean, preprocess, and structure datasets for model training, fine-tuning, and evaluation across different AI use cases.
Validate model outputs, perform error analysis, and help define and track quality benchmarks for accuracy, latency, and reliability.
Prepare clear technical documentation for workflows, APIs, and integration steps to support handoffs to engineering and product teams.
Benchmark models for accuracy, latency, scalability, and cost; summarize findings and recommendations in concise reports.
Develop a functional AI agent prototype to streamline internal workflows and knowledge access.
Build a RAG-based system that uses vector databases for intelligent, context-aware knowledge retrieval.
Implement a document analysis pipeline to extract structured data from healthcare documents.
Deliver prototypes, documentation, and performance reports for assigned AI use cases.