WRS Health is looking for an AI Engineer to join our team and contribute to the enhancement of our AI-driven Electronic Health Record (EHR) systems. This role focuses on developing and refining AI prompts to improve natural language processing (NLP) applications for healthcare workflows and building applications that enhance user interactions with language-based data.

What You'll Do

Develop and refine prompts to ensure optimal performance of Large Language Models (LLMs) in healthcare applications.
Experiment with various prompt strategies and assess their impact on model responses.
Collaborate with developers and domain experts to integrate LLM capabilities into WRS Health's EHR platforms.
Ensure prompts support accurate, context-aware responses tailored to healthcare-specific needs.
Evaluate and analyze model outputs to identify inconsistencies or areas for improvement.
Collaborate with data scientists to fine-tune models using healthcare-specific datasets.
Work closely with healthcare professionals and cross-functional teams to ensure LLMs align with user needs.
Educate internal teams on prompt engineering best practices and AI applications in healthcare.
Document prompt engineering methodologies, experiments, and outcomes for future reference.
Regularly report progress, challenges, and insights to stakeholders.

What We're Looking For

Bachelor's or Master's degree in Computer Science, Data Science, Computational Linguistics, or a related field.
Proven experience with prompt engineering and fine-tuning Large Language Models (e.g., OpenAI GPT, Claude, Llama).
Proven experience in developing and deploying machine learning models.
Strong programming skills in Python and other relevant languages.
Proficiency in Python and NLP libraries (e.g., Hugging Face, spaCy, NLTK).
Familiarity with APIs for interacting with LLMs and cloud platforms.
Knowledge with Lang Chain or other following LLM system building framework such as LlamaIndex, AgentGPT, Flowise, Tensorflow, GPT3 by OpenAI and others.
Background in Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps).
Strong problem-solving and analytical abilities.
Excellent communication skills and the ability to work in cross-functional teams.
Detail-oriented with a focus on delivering high-quality solutions.

Nice to Have

Hands-on experience in developing and deploying NLP models, particularly in the healthcare domain, is a plus.
Understanding of healthcare terminology and workflows is highly desirable.