Description

Responsibilities

Experience: 7+ years in AI development/architecture, with a focus on Generative AI and large-scale deep learning systems.

Technical skills:

  • LLMs and Generative Models: Proven expertise in LLMs (customization, fine-tuning), Retrieval-Augmented Generation (RAG), and other generative models like GANs and Diffusion Models.
  • Programming: Proficient in Python and deep learning frameworks like PyTorch or TensorFlow.
  • NLP: Advanced understanding of modern NLP techniques, such as transformer models and tokenization.
  • Cloud: Extensive experience with cloud platforms (AWS, Azure, GCP) and their respective AI/ML services (e.g., SageMaker, Vertex AI).
  • MLOps & Infrastructure: Experience with MLOps practices and building high-availability, low-latency systems using containers (Docker, Kubernetes) and microservices.
  • Monitor and increase the performance of RAG system.
  • Understand the basics of RAG and how to validate its output.
  • Determine how to increase the accuracy of RAG.
  • Identify general tools/techniques that will be used on the back for retrieving/generating the data.