Postdoc in Multimodal AI & Knowledge Reasoning

Exxon Mobil; Spring (TX); On-site; USD 65,000 - 90,000; Full time

Job summary

ExxonMobil is seeking a Postdoctoral Researcher in Spring, TX, to advance multimodal knowledge extraction and reasoning. You will develop AI methods to fuse text, images, video, and data sources for decision support in engineering contexts.

The role targets recent PhD graduates with expertise in multimodal ML, knowledge representation, and reasoning systems, collaborating across teams to build scalable AI systems.

Qualifications

• PhD in Computer Science, AI, ML or related field required.
• Demonstrated research in multimodal ML or knowledge-based AI.
• Experience with transformers and foundation models.
• Strong programming in Python; experience with ML frameworks.

Responsibilities

• Develop methods for multimodal data fusion and representation learning across text, visual, spatial, and temporal data.
• Design models for knowledge extraction from unstructured and semi-structured data.
• Build neural and symbolic or hybrid reasoning systems.
• Develop LLM- and multimodal foundation models for knowledge understanding and reasoning.
• Construct and use knowledge graphs for decision support.
• Enable context-aware inference using heterogeneous data sources.
• Evaluate models for accuracy, robustness, and explainability.
• Collaborate with domain experts to translate knowledge into decision-support tools.
• Implement scalable ML pipelines and data engineering best practices.
• Communicate findings through reports and publications.

Skills

Multimodal learning

Knowledge graphs

Information extraction

Reasoning systems

Python

PyTorch

TensorFlow

JAX

Transformers

Communication

Education

PhD in Computer Science / AI / ML or related field

Tools

PyTorch

TensorFlow

JAX

Job description

ExxonMobil is seeking a Postdoctoral Researcher in Spring, TX, to advance multimodal knowledge extraction and reasoning. You will develop AI methods to fuse text, images, video, and data sources for decision support in engineering contexts.

The role targets recent PhD graduates with expertise in multimodal ML, knowledge representation, and reasoning systems, collaborating across teams to build scalable AI systems.