CMA CGM
Senior AI/ML Scientist - Generative AI and Knowledge Graphs
CMA CGM, Palo Alto, California, United States, 94301
SAP AI Product Engineering Lead
At SAP, we integrate AI technology with extensive industry-specific data and deep process knowledge to create innovative AI capabilities for all SAP applications. Large Language Models (LLMs) hold immense potential to change the way we work and develop products. They are reshaping the landscape of Machine Learning across various domains. SAP AI Product Engineering is responsible for designing central frameworks and cloud services such as Joule, Generative AI Hub, AI Core, and Document Information Extraction as the AI foundation for embedded AI throughout our portfolio in addition to our efforts towards SAP's foundation models, both our own tabular business models and building on top of partner LLMs, and generative AI technologies. The role: Unique opportunity to lead the development of Business AI Scenarios on SAP business data embedded in a rich and diverse business context. Ability to solve complex problems using LLMs + Knowledge Graphs with In-context learning and finetuning. Strong experience with data pre-processing, Information Retrieval, RAG and applying Agentic AI to improve Question Answering with multimodality. Experience with the latest advancements in the field of LLMs, Foundational Models, and Machine Learning, and apply the expertise to enhance the models and improve product quality. Define processes, methods, hypothesis, experiments and review results from the ground up with an understanding to put them together for End-to-End Foundational Models and LLMs. Collaborate cross-functionally with other teams to understand needs and requirements, ensuring the Foundation Models/LLMs align with strategic company objectives of embedding AI into our product portfolio. Establish and drive research collaborations with academic and commercial partners. Contribute to thought leadership in a revolutionary new data modality for Foundation Models and Generative AI. What you bring: PhD or master's degree in computer science, Artificial Intelligence, or other relevant disciplines. 8+ years of relevant experience in Machine Learning and 3 years in LLMs. Extensive experience with LLMs or Deep Learning as well as Machine Learning with Knowledge Graphs (e.g. GNNs). Deep understanding of issues and opportunities of applying Generative AI in a business context. Proficiency in Python, and experience with ML frameworks such as PyTorch, TensorFlow, or similar. Experience in one of the agentic frameworks like LangGraph, etc Exceptional teamwork abilities, strong leadership and strategic thinking skills. Substantial publication record related to LLMs, Foundation Models, or Knowledge Graphs. Meet your team: SAP's AI organization is dedicated to seamlessly infusing AI into all enterprise applications, enabling customers, partners, and developers to enhance business processes and generate remarkable business value. Join our international AI team where innovation thrives, opportunities for personal development abound, and exceptional colleagues collaborate globally.
At SAP, we integrate AI technology with extensive industry-specific data and deep process knowledge to create innovative AI capabilities for all SAP applications. Large Language Models (LLMs) hold immense potential to change the way we work and develop products. They are reshaping the landscape of Machine Learning across various domains. SAP AI Product Engineering is responsible for designing central frameworks and cloud services such as Joule, Generative AI Hub, AI Core, and Document Information Extraction as the AI foundation for embedded AI throughout our portfolio in addition to our efforts towards SAP's foundation models, both our own tabular business models and building on top of partner LLMs, and generative AI technologies. The role: Unique opportunity to lead the development of Business AI Scenarios on SAP business data embedded in a rich and diverse business context. Ability to solve complex problems using LLMs + Knowledge Graphs with In-context learning and finetuning. Strong experience with data pre-processing, Information Retrieval, RAG and applying Agentic AI to improve Question Answering with multimodality. Experience with the latest advancements in the field of LLMs, Foundational Models, and Machine Learning, and apply the expertise to enhance the models and improve product quality. Define processes, methods, hypothesis, experiments and review results from the ground up with an understanding to put them together for End-to-End Foundational Models and LLMs. Collaborate cross-functionally with other teams to understand needs and requirements, ensuring the Foundation Models/LLMs align with strategic company objectives of embedding AI into our product portfolio. Establish and drive research collaborations with academic and commercial partners. Contribute to thought leadership in a revolutionary new data modality for Foundation Models and Generative AI. What you bring: PhD or master's degree in computer science, Artificial Intelligence, or other relevant disciplines. 8+ years of relevant experience in Machine Learning and 3 years in LLMs. Extensive experience with LLMs or Deep Learning as well as Machine Learning with Knowledge Graphs (e.g. GNNs). Deep understanding of issues and opportunities of applying Generative AI in a business context. Proficiency in Python, and experience with ML frameworks such as PyTorch, TensorFlow, or similar. Experience in one of the agentic frameworks like LangGraph, etc Exceptional teamwork abilities, strong leadership and strategic thinking skills. Substantial publication record related to LLMs, Foundation Models, or Knowledge Graphs. Meet your team: SAP's AI organization is dedicated to seamlessly infusing AI into all enterprise applications, enabling customers, partners, and developers to enhance business processes and generate remarkable business value. Join our international AI team where innovation thrives, opportunities for personal development abound, and exceptional colleagues collaborate globally.