Postdoctoral AI Scientist

NTT DATA AIVista

. Define and independently drive research questions across AIVista's science focus areas .

Posted 10/23/2026internshipPalo Alto • California • United StatesMid-LevelSenior💰 $150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and evaluating machine learning algorithms and AI systems, with a strong emphasis on experimental design and empirical research. Proven ability to communicate complex scientific findings and collaborate across multidisciplinary teams.

Highest-signal resume keywords

PhD In Computer ScienceMachine Learning ExpertisePython ProficiencyResearch Publication RecordExperimental Design Skills

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AlgorithmsStatistical MethodsEmpirical ResearchLarge Language ModelsKnowledge RepresentationFormal MethodsReinforcement LearningSimulationProcess MiningGraph Learning

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationCollaboration Skills

Industry Keywords

AI SystemsInspectable AIControlled EvaluationPrivacy-Preserving LearningHuman-In-The-Loop SystemsDigital TwinsRobust BenchmarkingMulti-Agent SystemsContext EngineeringGraduated-Autonomy Deployments

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Define and independently drive research questions across AIVista's science focus areas
Develop novel algorithms, models, methods, prototypes, and system designs
Evaluate research through rigorous experimentation
Design experiments and benchmarks measuring correctness, robustness, calibration, privacy, latency, cost, and process outcomes
Translate enterprise data, policies, feedback, and operational constraints into research problems, research artifacts, and deployable systems
Develop inspectable AI systems and analyses connecting model and agent decisions to evidence, rules, and outcomes
Move promising research from experimentation through simulation, controlled evaluation, and potential production-scale application
Communicate research findings internally and externally
Contribute research to leading conferences, journals, and the broader scientific community
Collaborate with AIVista's broader research agenda while developing an independent body of research

Requirements

What you’ll need

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 evidenced through 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
Relevant additional research experience may include neurosymbolic methods, autoformalization, formal verification, theorem proving, constraint solving, ontology construction, knowledge graphs, entity resolution, graph learning, graph-based retrieval, mid-training, supervised fine-tuning, preference optimization, reinforcement learning, synthetic data and task generation, verifiable reward design, scalable training and evaluation pipelines, agent memory, context engineering, model routing and orchestration, planning, tool use, multi-agent systems, continual/federated/privacy-preserving learning, uncertainty calibration, human-in-the-loop systems, regression-safe adaptation, process mining, digital twins, simulation, workflow systems, graduated-autonomy deployments, robust benchmarking, agentic environment construction, complex task metric design, or AI systems deployed in regulated, safety-sensitive, or high-stakes environments

Benefits

Comp & perks

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 to eligible postdoctoral researchers
Opportunity to pursue publication at top-tier conferences and journals
12-month appointment with option to extend to 24 months