Postdoctoral AI Scientist

NTT DATA AIVista • Palo Alto, CA

2d • Onsite

About The Position

AIVista, Inc., a wholly owned subsidiary of NTT DATA based in Palo Alto, develops AI products for enterprises operating in complex regulatory environments. The Postdoctoral AI Scientist conducts research on foundational problems at the intersection of machine learning, knowledge representation, formal methods, and AI agents for enterprise systems. The scientist works with researchers and engineers to define and pursue research questions, develop methods and systems, and evaluate them against complex, production-scale problems and data. The role aims to advance the state of the art while contributing to performant and trustworthy AI systems for real enterprise environments.

This is an initial 12-month postdoctoral research appointment, with an option to extend to 24 months. It is designed for researchers who have completed a PhD and want to develop a strong research agenda while working closely with real-world AI systems. Publication at top-tier conferences and journals is encouraged, and projects are selected to support scientific contribution and practical relevance.

Research areas include neurosymbolic methods and trustworthy reasoning; knowledge representation and semantic AI; adaptive and model-agnostic AI systems; scalable development of domain-specialized models; learning from human and operational feedback; evaluation, verification, and interpretability; and AI for complex workflows. The role involves independently driving research, developing and evaluating algorithms and systems, designing rigorous experiments and benchmarks, translating enterprise data and constraints into research problems and deployable systems, and communicating findings to scientific and industry audiences.

Requirements

• PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Applied Mathematics, Electrical or Computer Engineering, Operations Research, or a closely related technical field; the PhD must be completed before the appointment starts.
• Demonstrated research record in machine learning, artificial intelligence, computer science, or a related technical discipline, evidenced by peer-reviewed publications, significant research projects, or comparable scientific contributions.
• Strong foundations in machine learning, algorithms, statistical methods, experimental design, and empirical research.
• Deep research experience in one or more of: large language models, knowledge representation or knowledge graphs, formal methods, agentic systems, continual learning, multimodal learning, evaluation and interpretability, or process mining.
• Ability to independently formulate research questions, design rigorous experiments, analyze results, and communicate scientific findings.
• Proficiency in Python and experience implementing and evaluating machine learning or AI systems.
• Strong written and verbal communication skills and ability to collaborate effectively across research, engineering, and domain teams.

Nice To Haves

• Research experience in neurosymbolic methods, autoformalization, formal verification, theorem proving, or constraint solving.
• Research experience in ontology construction, knowledge graphs, entity resolution, graph learning, or graph-based retrieval.
• Research experience in mid-training (continued pretraining), supervised fine-tuning, preference optimization, or reinforcement learning for domain-specialized models.
• Research experience in synthetic data and task generation, verifiable reward design, or scalable pipelines for training and evaluating domain models.
• Research experience in agent memory, context engineering, model routing and orchestration, planning, tool use, or multi-agent systems.
• Research experience in continual, federated, or privacy-preserving learning; uncertainty calibration; human-in-the-loop systems; or regression-safe adaptation.
• Research experience in process mining, digital twins, simulation, workflow systems, or graduated-autonomy deployments.
• Research experience in 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.

Responsibilities

• Define and independently drive research questions across one or more AIVista science focus areas.
• Develop novel algorithms, models, methods, prototypes, and system designs, and evaluate their effectiveness through rigorous experimentation.
• Design experiments and benchmarks measuring correctness, robustness, calibration, privacy, latency, cost, and process outcomes.
• Work with scientists, engineers, and domain experts to translate enterprise data, policies, feedback, and operational constraints into research problems, research artifacts, and deployable systems.
• Develop inspectable AI systems and analyses that connect model and agent decisions to evidence, rules, and outcomes.
• Advance promising research from early experimentation through simulation, controlled evaluation, and potential application in production-scale AI systems.
• Communicate research findings internally and externally and contribute research to leading conferences, journals, and the broader scientific community.
• Collaborate with and contribute to AIVista's broader research agenda while developing an independent body of research during the appointment.

Benefits

• Company-sponsored benefits for eligible employees, in accordance with Company policies.
• Housing and relocation assistance may be available depending on individual circumstances and business needs.
• Eligible postdoctoral researchers may receive travel assistance associated with relocation to and from the Palo Alto area, in accordance with Company policy.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree