Staff Data Scientist

Essential functions

• Python

• Prompt engineering

• Must have 2+ working experience on Gen AI (LLM, RAG, LoRA, Deep learning  etc. )

• 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)

Qualifications

• 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.

Would be a plus

• 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.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

About us

Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.