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Diffco is seeking a highly skilled Generative AI Engineer to join our team in Silicon Valley. As a key member of our team, you will be responsible for developing and fine-tuning large language models (LLMs) for industry-specific applications. Your expertise in transformer-based architectures and fine-tuning models will enable us to create accurate and reliable AI solutions.
About the Role:
We are looking for an engineer who can design, train, and fine-tune models with minimal hallucinations and high accuracy. The ideal candidate should have a strong understanding of dynamic prompt engineering, retrieval-augmented generation (RAG), and knowledge base development. Your responsibilities will include developing and fine-tuning open-source LLMs, optimizing AI models to reduce hallucinations and increase domain-specific accuracy, implementing dynamic prompt engineering to control model responses, and integrating LLMs into a structured AI pipeline. Additionally, you will research, evaluate, and deploy NLP-based solutions for text classification, entity recognition, and semantic search, ensuring that models adhere to enterprise standards of accuracy, compliance, and security. You will work closely with DevOps engineers to scale AI solutions in production and optimize model inference efficiency for deployment in cloud-based and on-prem environments.
Must-Have Skills & Experience:
To succeed in this role, you must have strong experience with LLMs, NLP, and transformer-based architectures. Hands-on experience in fine-tuning and optimizing models using Hugging Face, PyTorch, TensorFlow, or LangChain is also essential. Proficiency in Python, PyTorch, TensorFlow, or JAX is required, as well as familiarity with vector databases and retrieval-augmented generation. You should have a strong background in statistical modeling and machine learning algorithms, and knowledge of MLOps tools for deployment and monitoring. Strong communication skills and the ability to collaborate with cross-functional teams are also necessary.