Staff Data Scientist

Summary

Join our dynamic and global Digital Product Engineering company as we scale! We build innovative products and experiences, and we're looking for talented colleagues to join our team. This role requires proficiency in Python and associated data science libraries, a strong understanding of AI, machine learning, and natural language processing, and experience with foundation models and LLMs. You will leverage your expertise in building and querying knowledge bases, working with text embeddings, and implementing RAG systems. We are seeking individuals with experience in handling various document formats and extracting structured information from unstructured data. This is a challenging and rewarding opportunity to contribute to cutting-edge projects.

Requirements

Possess skills in Python for Data Science

Responsibilities

• Proficiently use Python and all associated DS libraries and frameworks
• Demonstrate strong knowledge in AI, machine learning, and natural language processing
• Leverage, train, and fine-tune Foundation Models, including multimodal inputs and outputs
• Work with key LLM models APIs (e.g., OpenAI, Anthropic) and LLM Frameworks (e.g., LangChain, LlamaIndex)
• Utilize multi-agent frameworks/systems and understand multi-agent systems and their applications in complex problem-solving scenarios
• Use unstructured.io or similar libraries for handling various document formats and extracting structured information from unstructured data
• Utilize Llama Index for building and querying knowledge bases, including its data connectors, indexing strategies, and query engines
• Employ effective text chunking techniques for optimal processing and indexing of large documents or datasets
• Generate and work with text embeddings using models like BERT, GPT, or domain-specific embedding models
• Understand embedding spaces and their applications in semantic search and information retrieval
• Construct and query knowledge graphs, including technologies like Neo4j or RDF triplestores
• Understand ontology design and graph-based reasoning
• Apply RAG concepts and fundamentals (vectorDBs, semantic search, etc.)
• Implement RAG systems that combine knowledge bases with generative AI models

Preferred Qualifications

• Have skills in Machine Learning on AWS
• Possess knowledge of Generative AI Fundamentals