AI Innovator and Application Builder

1 week ago

Bengaluru, Karnataka, India beBeeGenerative Full time
Job Overview

We are seeking a highly skilled Senior Generative AI Developer to join our mission-driven team. This role focuses on leveraging cutting-edge Generative AI (GenAI) technologies to drive innovation and efficiency in software development and business processes.

Key Responsibilities
  • Develop and deploy GenAI-based applications to solve complex business problems.
  • Implement RAG frameworks to enhance information retrieval and response accuracy.
  • Design and optimize document chunking strategies tailored to specific data types and use cases.
  • Build and manage data embeddings using various vector databases for high-performance similarity searches.
  • Collaborate with data engineers and scientists to integrate AI solutions seamlessly into existing pipelines.
  • Explore and implement best practices for leveraging Amazon Bedrock and Azure OpenAI services.
Required Skills and Qualifications
  • Proficiency in Generative AI frameworks and technologies like
  • Prompt Engineering creating specific prompts to guide LLM outputs
  • Fine Tuning and Few-Shot learning Adapting LLMs for domain-specific tasks.
  • Retrieval-Augmented Generation (RAG) Combining LLMs with external data retrieval systems
  • Text-to-Text Transfer Transformation (T5) Framework for translating tasks into text forms.
  • Expertise in designing and implementing chunking strategies for diverse datasets.
  • Strong knowledge of data embedding techniques and working experience with vector databases like Pinecone, Weaviate, or Milvus.
  • Solid programming skills in Python, with experience in AI/ML libraries such as TensorFlow, PyTorch, or Hugging Face Transformers.
  • Familiarity with cloud platforms and services for AI/ML workloads (AWS or Azure).
  • Experience with API integration for AI services and building scalable applications
What You Should Expect
  • Develop and deploy GenAI-based applications to solve complex business problems.
  • Implement RAG frameworks to enhance information retrieval and response accuracy.
  • Design and optimize document chunking strategies tailored to specific data types and use cases.
  • Build and manage data embeddings using various vector databases for high-performance similarity searches.
  • Collaborate with data engineers and scientists to integrate AI solutions seamlessly into existing pipelines.
  • Explore and implement best practices for leveraging Amazon Bedrock and Azure OpenAI services.

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