Generative AI Researcher

hace 2 días


Buenos Aires, Buenos Aires C.F., Argentina Diffco US, Inc. A tiempo completo
About the Position:
As a key member of our team, you will be responsible for designing, training, and fine-tuning models while ensuring minimal hallucinations and high accuracy. You will also be well-versed in dynamic prompt engineering, retrieval-augmented generation (RAG), and knowledge base development.

Key Responsibilities:
  • Develop and fine-tune open-source LLMs (Mistral, Zephyr, Llama) for insurance-specific applications.
  • Optimize AI models to reduce hallucinations and increase domain-specific accuracy.
  • Implement dynamic prompt engineering to control model responses and improve reliability.
  • Integrate LLMs into a structured AI pipeline (RAG, knowledge retrieval, vector databases).
  • Research, evaluate, and deploy NLP-based solutions for text classification, entity recognition, and semantic search.
  • Ensure models adhere to enterprise standards of accuracy, compliance, and security (GDPR, CCPA, PII handling).
  • Work with large datasets to train models efficiently and integrate them into real-world applications.
  • Optimize model inference efficiency for deployment in cloud-based and on-prem environments.

Required Qualifications:
  • Strong experience with LLMs, NLP, and transformer-based architectures.
  • Hands-on experience in fine-tuning and optimizing models (Hugging Face, PyTorch, TensorFlow, LangChain, etc.).
  • Proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Familiarity with vector databases (Weaviate, Pinecone, FAISS) and retrieval-augmented generation (RAG).
  • Understanding of prompt engineering strategies to minimize hallucinations.
  • Strong background in statistical modeling and machine learning algorithms.
  • Knowledge of MLOps tools for deployment and monitoring (MLflow, Kubeflow, Ray).

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