Postdoctoral AI Scientist

The role

You will conduct research on foundational problems at the intersection of machine learning, knowledge representation, formal methods, and AI agents for enterprise systems. You will develop new methods and systems and evaluate them against complex, production-scale problems and data.

What you will do

• Define and independently drive research questions across science focus areas.
• Develop novel algorithms, models, methods, prototypes, and system designs.
• Design experiments and benchmarks to measure correctness, robustness, calibration, privacy, latency, cost, and process outcomes.
• Work with scientists, engineers, and domain experts to translate enterprise data and constraints into research artifacts.
• Develop inspectable AI systems and analyses.
• Move research from early experimentation through simulation to potential production-scale application.
• Communicate research findings internally and externally.
• Collaborate with and contribute to AIVista's broader research agenda.

Required qualifications

• PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Applied Mathematics, Electrical or Computer Engineering, Operations Research, or a closely related technical field.
• PhD must be completed prior to the start of the appointment.
• Demonstrated research record in machine learning, artificial intelligence, computer science, or a related technical discipline.
• Strong foundations in machine learning, algorithms, statistical methods, experimental design, and empirical research.
• Deep research experience in one or more of the following areas: large language models, knowledge representation or knowledge graphs, formal methods, agentic systems, continual learning, multimodal lea
• Ability to independently formulate research questions, design rigorous experiments, analyze results, and communicate scientific findings.
• Proficiency in Python.
• Experience implementing and evaluating machine learning or AI systems.
• Strong written and verbal communication skills.
• Ability to collaborate effectively across research, engineering, and domain teams.

Nice to have

• Neurosymbolic methods, autoformalization, formal verification, theorem proving, or constraint solving.
• Ontology construction, knowledge graphs, entity resolution, graph learning, or graph-based retrieval.
• Mid-training (continued pretraining), supervised fine-tuning, preference optimization, or reinforcement learning for building domain-specialized models.
• Synthetic data and task generation, verifiable reward design, or scalable pipelines for training and evaluating domain models.
• Agent memory, context engineering, model routing and orchestration, planning, tool use, or multi-agent systems.
• Continual, federated, or privacy-preserving learning; uncertainty calibration; human-in-the-loop systems; or regression-safe adaptation.
• Process mining, digital twins, simulation, workflow systems, or graduated-autonomy deployments.
• Robust and scalable benchmarking, agentic environment construction, and complex task metric design.
• Research involving AI systems deployed in regulated, safety-sensitive, or other high-stakes environments.

Benefits

• Company-sponsored benefits in accordance with applicable Company policies.
• Housing and relocation assistance may be available based on individual circumstances and business needs.
• Travel assistance associated with relocation to and from the Palo Alto area may be available for eligible postdoctoral researchers.

About the company

NTT DATA AIVista, Inc., a wholly owned subsidiary of NTT DATA, develops AI products for enterprises operating in complex regulatory environments. Based in Palo Alto, they combine deep AI product expertise with NTT DATA's industry knowledge and systems-integration experience.