Member of Technical Staff - Science I

The role

The Member of Technical Staff Scientist advances AI research and turns research results into production systems. Work spans large language models, multimodal AI, intelligent agents, graph machine learning, safety, alignment, and evaluation.

What you will do

• Execute the long-term AI research roadmap aligned with company strategy, product priorities, and measurable business outcomes.
• Define and prioritize technical research bets across LLMs, multimodal AI, agents, graph machine learning, knowledge graphs, safety, neurosymbolic reasoning, alignment, and evaluation.
• Develop algorithms for ontology induction, schema matching, entity resolution, semantic alignment, consistency checking, and incremental ontology evolution.
• Develop methods that connect learning-based models with symbolic rules, formal constraints, and typed enterprise knowledge.
• Design ontology-grounded agents that reason over typed objects and act through governed, auditable interfaces.
• Create evaluations for induction precision and recall, alignment correctness, rule faithfulness, semantic consistency, determinism, calibration, latency, cost, and customer outcomes.
• Implement algorithms and architectures that create competitive advantage and move experimental models into scalable production systems.
• Partner with engineering to design model deployment, evaluation, monitoring, and continuous improvement loops.
• Align scientific work with real customer problems and measurable operational outcomes.
• Lead research publications, patents, and open-source contributions when strategically valuable.

Required qualifications

• PhD in computer science, machine learning, artificial intelligence, mathematics, physics, or a related field, or equivalent industry impact.
• At least 5 years of experience in artificial intelligence or machine learning, with significant experience applying science and research in production environments.
• A proven record of impactful research demonstrated through publications, patents, or shipped AI products.
• Strong foundations in machine learning, algorithms, statistical methods, experimental design, and scientific evaluation.
• Deep experience in at least one relevant area: LLMs, agents, multimodal learning, graph machine learning, knowledge representation, formal methods, process mining, or AI evaluation.
• Proficiency in Python and experience building research prototypes that engineering teams can transition to production.

Nice to have

• Experience with ontology construction or evolution, knowledge graphs, entity resolution, schema matching, graph reasoning, or graph-based retrieval.
• Experience with the Web Ontology Language (OWL), Resource Description Framework (RDF), description logics, semantic query languages, or ontology validation methods.
• Experience with neurosymbolic methods, autoformalization, formal verification, theorem proving, satisfiability modulo theories (SMT), constraint solving, or policy engines.
• Experience integrating enterprise data models, SOR schemas, application programming interfaces, and unstructured documents into common semantic representations.
• Familiarity with process mining, Business Process Model and Notation (BPMN), workflow systems, simulation, or digital twins.
• Experience designing evaluations where correctness, determinism, provenance, auditability, and safe failure behavior matter as much as model capability.
• Experience deploying AI systems in regulated or high-stakes domains

Benefits

• Medical, dental, and vision insurance
• 401(k) plan
• Significant Company HSA contribution
• Paid holidays
• Flexible PTO

About the company

NTT DATA AIVista, Inc., a wholly owned subsidiary of NTT DATA, is based in Silicon Valley. They develop AI products for enterprises operating in complex regulatory environments.