Job description
Summary
We are seeking a highly skilled Python Generative AI Developer to join our AI/ML team. This role focuses on leveraging cutting-edge Generative AI (GenAI) technologies to drive innovation and efficiency in software development and business processes. The ideal candidate will work on advanced techniques such as Retrieval-Augmented Generation (RAG), document chunking, and data embedding across multiple vector databases. They will collaborate closely with cross-functional teams to design, implement, and optimize AI-driven solutions, with exposure to cloud-native AI platforms like Amazon Bedrock and Microsoft Azure OpenAI considered a plus
Your role in our mission
- 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.
- Stay updated on emerging trends and technologies in the GenAI and AI/ML landscape
What we're looking for
- 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 in this role
- 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.
- Stay updated on emerging trends and technologies in the GenAI and AI/ML landscape.
