Quantitative Researcher Machine Learning Jobs in Houston, TX

ExxonMobil is seeking a highly motivated Postdoctoral Researcher specializing in multimodal knowledge extraction and reasoning. The successful candidate will develop advanced AI methods to extract, integrate, and reason over information from diverse data sources—including text, images, video, time series, and structured data—to support critical business and engineering decisions.

This role is ideal for a recent Ph.D. graduate with expertise in multimodal machine learning, knowledge representation, and reasoning systems. The candidate will work in a collaborative environment to build next-generation AI systems that transform complex, heterogeneous data into actionable insights.

• Develop methods for multimodal data fusion and representation learning across text, visual, spatial, and temporal data.
• Design models for knowledge extraction, including entity recognition, relation extraction, and structured information generation from unstructured and semi-structured data.
• Build reasoning systems that combine neural methods with symbolic or knowledge-based approaches.
• Develop and apply large language model (LLM)-based and multimodal foundation models for knowledge understanding and reasoning.
• Construct and utilize knowledge graphs and structured representations for enhanced reasoning and decision support.
• Enable context-aware inference and decision-making using heterogeneous data sources.
• Evaluate models for accuracy, robustness, and reasoning capability, including explainability where relevant.
• Collaborate with domain experts to translate extracted knowledge into decision-support workflows.
• Implement scalable pipelines using modern ML frameworks and data engineering best practices.
• Communicate findings through technical reports, journal publications, and conference presentations.

• Multimodal machine learning and cross-modal representation learning
• Knowledge extraction from text, images, and sensor data
• Knowledge graphs and graph-based reasoning
• Neural-symbolic AI and hybrid reasoning systems
• Large language models and multimodal foundation models
• Information retrieval, semantic search, and question answering
• Temporal and causal reasoning in complex systems
• Applications to engineering, scientific, and industrial data environments

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field, with a focus on multimodal learning, knowledge extraction, or reasoning.
• Demonstrated research experience in multimodal machine learning and/or knowledge-based AI, including one or more of:
  • • Multimodal representation learning
    • Information extraction or natural language understanding
    • Knowledge graphs or structured representations
    • Reasoning systems (neural, symbolic, or hybrid)
• Experience with modern deep learning architectures, including transformers and foundation models.
• Strong programming skills in Python.
• Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Experience working with heterogeneous datasets (text, images, structured data, etc.).
• Strong analytical, problem-solving, and communication skills.
• Ability to work effectively in multidisciplinary teams.

• Experience with multimodal foundation models or large language models (LLMs).
• Familiarity with knowledge graph construction, querying, and reasoning frameworks.
• Experience with retrieval-augmented generation (RAG) or hybrid search systems.
• Background in probabilistic reasoning, causal inference, or uncertainty-aware AI.
• Experience with scalable data pipelines and distributed ML systems.
• Experience applying AI methods to scientific, engineering, or industrial datasets.
• Strong publication record in multimodal AI, NLP, or knowledge-based systems.
• Demonstrated ability to translate research into practical decision-support tools.

This opportunity is for a postdoctoral position expected to last one to three years, subject to annual review and renewal.

Our post doctoral research employees are located at our main corporate office in Spring, Texas.

An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance, and life. Individual pay is determined based on various factors including degree/education, discipline, year of study, skills, abilities, qualifications, and work experience. 

More information on our Company’s benefits can be found at www.exxonmobilfamily.com.

Please note pay rates and benefits may be changed from time to time without notice, subject to applicable law.

Relocation benefits may be available to you based on ExxonMobil eligibility guidelines. 

ExxonMobil is an Equal Opportunity Employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability.