AI/LLM Developer/Engineer
AI/LLM Developer/Engineer
Posted on :
31-07-2025
Employer Active
1 Vacancy
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Monthly Salary
$ 26 - 33
Vacancy
1 Vacancy
Posted on :
31-07-2025
Job Description
Position Summary
The Center for Virtual Care Value and Excellence (ViVE) led by Dr. Saif Khairat is seeking an AI/ LLM Developer/Engineer to join our AI research team. This is an exciting opportunity to contribute to innovative projects at the forefront of healthcare delivery improvement leveraging Large Language Models (LLMs) and clinical data analysis. About the Position We are looking for individuals with a strong theoretical and practical background in large language models machine learning and natural language processing combined with a collaborative spirit and a drive for problem-solving. Youll join a multidisciplinary team that values diversity and brings together expertise in software engineering big data clinical informatics and medicine. Key Responsibilities Design fine-tune and evaluate large language models (LLMs) tailored to domain-specific applications using techniques such as transfer learning LoRA and reinforcement learning with human feedback ( RLHF ). Build intelligent applications powered by LLMs including chatbots virtual agents clinical decision tools or document analyzers using frameworks like LangChain LlamaIndex or semantic search pipelines. Develop scalable LLM pipelines and infrastructure including data ingestion preprocessing model serving (via GPU / TPU ) and continuous performance monitoring. Integrate commercial and open-source LLMs (e.g. OpenAI GPT Claude Mistral LLaMA) via APIs or local deployment into digital health or enterprise systems. Craft and iterate prompts using advanced prompt engineering and chain-of-thought strategies to improve output relevance tone factuality and task completion. Implement retrieval-augmented generation ( RAG ) architectures to enhance context awareness using vector databases (e.g. Pinecone FAISS Weaviate). Evaluate LLM performance using automated and human-in-the-loop methods to assess accuracy hallucination safety and user satisfaction. Collaborate across disciplines with data scientists UX designers domain experts and MLOps to ensure usability performance and alignment with real-world needs. Monitor and optimize system performance including latency throughput token usage and model cost-effectiveness across deployment environments. Stay current with advancements in generative AI contributing to the internal knowledge base and driving adoption of best practices for ethical and responsible LLM use.
Required Qualifications Competencies And Experience
Expertise in Retrieval-Augmented Generation ( RAG ) Natural Language Processing ( NLP ) deep learning frameworks. Proficiency in Python and frameworks such as PyTorch TensorFlow Hugging Face Transformers or LangChain Familiarity with clinical or healthcare data (e.g. EHRs clinical notes structured claims data) Proven research record with peer-reviewed publications in relevant fields Strong problem-solving skills and the ability to work in a collaborative environment.
Preferred Qualifications Competencies And Experience
Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models HITL techniques and prompt engineering. Experience with LLM fine-tuning prompt engineering or retrieval-augmented generation ( RAG ) Experience deploying large-scale machine learning models in cloud environments.
The Center for Virtual Care Value and Excellence (ViVE) led by Dr. Saif Khairat is seeking an AI/ LLM Developer/Engineer to join our AI research team. This is an exciting opportunity to contribute to innovative projects at the forefront of healthcare delivery improvement leveraging Large Language Models (LLMs) and clinical data analysis. About the Position We are looking for individuals with a strong theoretical and practical background in large language models machine learning and natural language processing combined with a collaborative spirit and a drive for problem-solving. Youll join a multidisciplinary team that values diversity and brings together expertise in software engineering big data clinical informatics and medicine. Key Responsibilities Design fine-tune and evaluate large language models (LLMs) tailored to domain-specific applications using techniques such as transfer learning LoRA and reinforcement learning with human feedback ( RLHF ). Build intelligent applications powered by LLMs including chatbots virtual agents clinical decision tools or document analyzers using frameworks like LangChain LlamaIndex or semantic search pipelines. Develop scalable LLM pipelines and infrastructure including data ingestion preprocessing model serving (via GPU / TPU ) and continuous performance monitoring. Integrate commercial and open-source LLMs (e.g. OpenAI GPT Claude Mistral LLaMA) via APIs or local deployment into digital health or enterprise systems. Craft and iterate prompts using advanced prompt engineering and chain-of-thought strategies to improve output relevance tone factuality and task completion. Implement retrieval-augmented generation ( RAG ) architectures to enhance context awareness using vector databases (e.g. Pinecone FAISS Weaviate). Evaluate LLM performance using automated and human-in-the-loop methods to assess accuracy hallucination safety and user satisfaction. Collaborate across disciplines with data scientists UX designers domain experts and MLOps to ensure usability performance and alignment with real-world needs. Monitor and optimize system performance including latency throughput token usage and model cost-effectiveness across deployment environments. Stay current with advancements in generative AI contributing to the internal knowledge base and driving adoption of best practices for ethical and responsible LLM use.
Required Qualifications Competencies And Experience
Expertise in Retrieval-Augmented Generation ( RAG ) Natural Language Processing ( NLP ) deep learning frameworks. Proficiency in Python and frameworks such as PyTorch TensorFlow Hugging Face Transformers or LangChain Familiarity with clinical or healthcare data (e.g. EHRs clinical notes structured claims data) Proven research record with peer-reviewed publications in relevant fields Strong problem-solving skills and the ability to work in a collaborative environment.
Preferred Qualifications Competencies And Experience
Distributed parallel training and parameter-efficient tuning. Familiarity with multi-modal foundation models HITL techniques and prompt engineering. Experience with LLM fine-tuning prompt engineering or retrieval-augmented generation ( RAG ) Experience deploying large-scale machine learning models in cloud environments.
Required Experience:
Staff IC
Employment Type
Full-Time
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