Data Scientist

Job Description

Role & responsibilitiMes Candiate needs to be 8+ Years of Experience Details on tech stack Python Prompt engineering Best practices for prompt engineering How LLM can be used in applications for a variety of tasks NLP Understanding of typical NLP problems: classification, NER, summarization, question answering, sentiment analysis, etc. Theoretical intuitive understanding of how Transformers work (tokenization, attention, etc). Word and sentence embeddings Vector search Vector databases, performance tuning Document chunking techniques LLM applications development LangChain, LlamaIndex Chain of Thoughts, DSP, and other techniques Agents and tools Google cloud (GCP) Nice to have requirements to the candidate Preferable, the engineers are expected to have IT services/consulting experience. Proficient in developing LLM-powered systems using advanced prompt engineering techniques, RAG and agentic design patterns. Experienced with frameworks like LangChain, LlamaIndex, and DSPy. Familiar with evaluation approaches and metrics for different types of LLM-based systems. Experienced with keyword and vector search methods, including understanding of their underlying algorithms. Familiar with popular vector search engines. Competent in various document understanding models and techniques to parse complex documents and implement effective chunking strategies for RAG systems. Familiar with LLM and embedding models fine-tuning techniques. Competent in using joint vision-language and generative models to solve various problems related to image generation, visual question answering, and multi-modal search. Familiar with diffusion models and associated techniques like LoRA, Dreambooth, and ControlNet. Understanding of the challenges and risks associated with the development of Generative AI systems and how to mitigate them. Familiar with various architecture design patterns for different types of LLM-based applications such as chatbots, text2sql, document understanding, etc. Familiar with various approaches to scalability and cost reduction in Generative AI systems. Ability to stay updated with the latest advancements in Generative AI and integrate emerging technologies to drive innovation and improve the performance of AI systems. Familiar with Responsible AI principles and Human-AI interaction design best practices. Preferred candidate profile