Artificial Intelligence Intern (NLP)

Hiring: AI/NLP Intern – Clinical Note Generation & LLM Evaluation (Remote)

📅 Start: ASAP | 🕒 Duration: 3–6 months | 💼 Unpaid (Potential for paid extension)

medical documentation, patient monitoring, and insurance workflows

AI/NLP intern

• Fine-tune & benchmark LLMs (LLaMA, Mistral, MedAlpaca)
• Evaluate models using BLEU, ROUGE, BERTScore, and factuality
• Build NER + entity linking pipelines
• Deploy APIs (FastAPI) and work with front-end engineers
• Run error analyses, iterate prompts, explore new ideas

• Python + HuggingFace Transformers + basic ML/NLP
• Understanding of prompting, attention, tokenization
• Jupyter or Colab for experimentation

• FastAPI, React, full-stack experience
• Knowledge of clinical NLP or biomedical informatics

We shortlist candidates via a hands-on task using the ACI-Bench dataset (doctor–patient conversations → SOAP notes). You'll benchmark open-source LLMs and submit a short report or notebook. Details sent after initial screening. But, proactive candidates can already:

1. Understand the Data : https://github.com/wyim/aci-bench/blob/main/data/challenge_data/train.csv
2. Analyze the format of the doctor-patient encounters and how they map to the structured clinical notes.
3. Explore the narrative and SOAP-style elements in the provided notes.
4. Select and Apply LLMs - Choose one or more open-source LLMs (e.g., LLaMA, Mistral, MedAlpaca) that can be used to generate notes from the conversations.
5. Decide whether to use zero-shot prompting, few-shot learning, or fine-tuning approaches.
6. Define Evaluation Metrics - focus on hallucination and faithfulness

• Work on real AI-for-healthcare systems
• Mentorship from experts
• High-impact portfolio project
• Strong LoR + possible transition to paid contract

Apply by sending your resume + GitHub (if any) + a short blurb on your NLP experience to [founder@saans.ai].

Let’s build the future of clinical care—together. 🚀

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