Fine-tune and evaluate LLMs for healthcare use cases.
Build multimodal AI systems integrating text, structured data, and images.
Optimize models for accuracy, latency, and efficiency in production.
Integrate STT and TTS into conversational interfaces.
Customize foundation models using domain adaptation and prompt techniques (LoRA).

🎯 Requirements

Bachelor's or Master's in CS, ML, AI, or related field.
2+ years in end-to-end AI/ML lifecycle.
Healthcare software development experience with EHR exposure.
Experience deploying AI with real-world healthcare data.
Experience building voice assistants or conversational AI.
Python with PyTorch or TensorFlow; NLP/NLU experience.

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