- Company Name
- Monark
- Job Title
- AI/ML/LLM Engineer (Healthcare & Edge AI)
- Job Description
-
**Job Title**
AI/ML/LLM Engineer (Healthcare & Edge AI)
**Role Summary**
Design, train, fine‑tune, and deploy large language models and multimodal machine learning solutions for clinical decision‑support. Optimize models for edge platforms (e.g., NVIDIA Jetson) and build scalable pipelines with PyTorch, TensorFlow, and Hugging Face frameworks.
**Expectations**
- Deliver production‑ready AI models for healthcare use.
- Ensure models meet clinical safety and performance standards.
- Collaborate across firmware, front‑end, and clinical teams.
- Maintain clear documentation and research records.
- Stay current with LLM advancements and edge deployment best practices.
**Key Responsibilities**
- Develop and train ML/LLM models for clinical NLP, computer vision, and time‑series analysis.
- Fine‑tune transformer‑based LLMs (e.g., LLaMA, GPT, BERT) on domain‑specific data.
- Fuse EMR notes, sensor data, and video into robust predictive systems.
- Optimize and deploy models on NVIDIA Jetson (Xavier, AGX Orin, etc.) using CUDA, TensorRT, ONNX.
- Build scalable training and inference pipelines with PyTorch, TensorFlow, and Hugging Face Transformers.
- Define metrics, conduct clinical validations, and iterate for safety‑critical environments.
- Work with firmware, front‑end, and clinical stakeholders; document processes and results.
**Required Skills**
- 3+ years AI/ML development, including NLP and LLMs.
- Proficiency in Python, PyTorch, and TensorFlow.
- Experience with Hugging Face Transformers, LangChain, or OpenLLM.
- Familiarity with NVIDIA CUDA, TensorRT, and ONNX for edge acceleration.
- Strong understanding of neural networks, interpretability, and training workflows.
- Version control (Git) and collaborative development practices.
- Knowledge of medical/clinical datasets (notes, time‑series, imaging) preferred.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Biomedical Engineering, or related field.
- Relevant certifications in AI/ML, deep learning, or cloud platforms are a plus.
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