GenAI Scientist`

Skills

Graduate degree in computer science data science engineering physics mathematics statistics or other quantitative fields 7+ years of experience in AI machine learning data science engineering and architecture with a proven track record to drive innovation and impacts Strong knowledge and experience with big data platforms (AWS Azure Spark) and ML/AI languages and tools (Python TensorFlow PyTorch) Experience working with technologies related to LLMs including architectures model evaluation pre-training and fine-tuning techniques Experience in design deployment and evaluation of LLM-powered AI agents and tools Experience in prompt engineering RAG open source frameworks for building applications with LLM like LangChain Develop operationalize measure and manage Gen AI models and maintain high system reliability & safety. Design solution architecture and develop compound AI systems for enterprise use cases. Build Gen AI prototypes PoCs and explore new applications across the organization. Communicate collaborate and build relationships with internal and partner teams to drive Gen AI adoption and implementation. Provide thought leadership to advance Gen AI research. Build partnership with academic and leading AI companies.

Description

Generative AI science will develop Gen AI solutions, fine-tune and build Gen AI models, and help enterprise functions leverage these models to power end applications. This role will partner closely with other data science and ML teams, digital and product teams, data analytics teams, engineering, and business functions across the organization to drive the development and implementation of innovative Gen AI models and systems.

Responsibilities

• Graduate degree in computer science, data science, engineering, physics, mathematics, statistics, or other quantitative fields
• 7+ years of experience in AI, machine learning, data science, engineering and architecture with a proven track record to drive innovation and impacts
• Strong knowledge and experience with big data platforms (AWS, Azure, Spark) and ML/AI languages and tools (Python, TensorFlow, PyTorch)
• Experience working with technologies related to LLMs including architectures, model evaluation, pre-training and fine-tuning techniques
• Experience in design, deployment, and evaluation of LLM-powered AI agents and tools
• Experience in prompt engineering, RAG, open source frameworks for building applications with LLM like LangChain
• Experience in developing large-scale AI/ML services