AI Scientist - Intern

Posted 23 Days Ago
7 Locations
Remote or Hybrid
150K-174K Annually
Internship
Artificial Intelligence • Machine Learning • Software • Automation
The Role
Research-focused internship for advanced PhD candidates to develop and evaluate neurosymbolic, knowledge representation, multimodal, and trustworthy AI methods. Duties include defining research questions, building prototypes and benchmarks, running rigorous experiments, collaborating with engineers and domain experts, and moving research toward production and publications.
Summary Generated by Built In

AI Scientist Intern

Palo Alto, California | 3-6 months

About AIVista

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, we combine deep AI product expertise with NTT DATA's industry knowledge and systems-integration experience, working with NTT companies to deploy solutions for enterprise clients.

The Opportunity

This research internship is designed for advanced PhD candidates who want to tackle foundational problems at the intersection of machine learning, knowledge representation, formal methods, and enterprise systems. You will work with scientists and engineers to turn research ideas into trustworthy AI capabilities evaluated on production-scale systems and data.

The internship lasts 3-6 months, with the possibility of extension. Pursuing top-tier conference publications is highly encouraged, and projects are selected to support both rigorous research andpractical relevance.

Science Focus

• Neurosymbolic methods and trustworthy reasoning: Combine learning-based and symbolic techniques to improve reliability, transparency, and alignment with domain constraints.

• Knowledge representation and semantic AI: Develop methods that help AI systems organize, connect, and reason over complex enterprise information.

• Adaptive and model-agnostic AI systems: Explore flexible approaches that integrate models, tools, context, and memory across diverse tasks and environments.

• Document and multimodal intelligence: Improve how AI systems understand and reason over information expressed across text, documents, images, and other modalities.

• Learning from feedback: Develop methods that enable AI systems to improve safely and

effectively from human and operational feedback.

• Evaluation, verification, and interpretability: Advance rigorous approaches to assessing AI

reliability, robustness, safety, and transparency.

• AI for complex workflows: Explore how intelligent systems can support and improve multi-step enterprise processes while maintaining appropriate oversight and control.

What You'll Do

• Define research questions and develop algorithms, prototypes, and system designs across one or more focus areas.

• Design rigorous experiments and benchmarks that measure correctness, robustness, calibration, privacy, latency, cost, and process outcomes.

• Work with scientists, engineers, and domain experts to turn enterprise data, policies, feedback, and operational constraints into research artifacts and deployable systems.

• Develop inspectable AI systems and analyses that connect model and agent decisions to

evidence, rules, and outcomes.

• Move promising research toward production through simulation and controlled evaluation, and contribute results to high-quality research publications.

Qualifications

• Advanced PhD candidate in computer science, machine learning, artificial intelligence, or a related field.

• A strong research record or demonstrated publication trajectory in relevant areas.

• Strong foundations in machine learning, algorithms, and statistical methods.

• Deep experience in at least one of the following: language models, knowledge representation or graphs, formal methods, agentic systems, continual learning, multimodal learning, or process mining.

• Proficiency in Python and experience designing and running rigorous empirical studies.

Preferred

• Experience with neurosymbolic methods, autoformalization, formal verification, theorem

proving, or constraint solving.

• Experience with ontology construction, knowledge graphs, entity resolution, graph learning, or graph-based retrieval.

• Experience with agent memory, context engineering, model routing or orchestration, planning, tool use, or multi-agent systems.

• Experience with continual, federated, or privacy-preserving learning; uncertainty calibration; human-in-the-loop systems; or regression-safe adaptation.

• Familiarity with process mining, digital twins, simulation, workflow systems, or graduated- autonomy deployments.

• Experience with robust and scalable benchmarking, agentic environment construction, and complex task metric design.

• Interest in bridging foundational research with deployed AI systems in regulated or high-stakes domains.

Compensation Details

The monthly compensation range for this role is $12,500–$14,500. Individual compensation is determined based on factors including education, experience, skills, qualifications, geographic location, and business needs. Eligible interns may receive relocation and housing assistance.

NTT DATA AIVista is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, ancestry,

sex, gender identity or expression, sexual orientation, age, disability, genetic information, marital status, military or veteran status,

reproductive health decisions, or any other characteristic protected under applicable federal, state, or local law.

Skills Required

  • Advanced PhD candidate in computer science, machine learning, AI, or related field
  • Strong research record or demonstrated publication trajectory
  • Strong foundations in machine learning, algorithms, and statistical methods
  • Deep experience in at least one: language models, knowledge representation/graphs, formal methods, agentic systems, continual learning, multimodal learning, or process mining
  • Proficiency in Python
  • Experience designing and running rigorous empirical studies
  • Experience with neurosymbolic methods, autoformalization, formal verification, theorem proving, or constraint solving
  • Experience with ontology construction, knowledge graphs, entity resolution, graph learning, or graph-based retrieval
  • Experience with agent memory, context engineering, model routing/orchestration, planning, tool use, or multi-agent systems
  • Experience with continual, federated, or privacy-preserving learning; uncertainty calibration; human-in-the-loop systems; or regression-safe adaptation
  • Familiarity with process mining, digital twins, simulation, workflow systems, or graduated-autonomy deployments
  • Experience with robust and scalable benchmarking, agentic environment construction, and complex task metric design
  • Interest in bridging foundational research with deployed AI systems in regulated or high-stakes domains
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The Company
125 Employees
Year Founded: 2025

What We Do

NTT DATA AIVista is a Silicon Valley-based, wholly owned NTT DATA subsidiary that helps regulated enterprises operationalize agentic AI responsibly and at scale. Its service-as-software platform combines domain-specific models and AI agents, an enterprise knowledge base, governance guardrails, and production deployment capabilities. The company targets mission-critical workflows, providing orchestration, observability, memory, runtime, and marketplace functions to support reliable, auditable enterprise AI operations.

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