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Applied AI Researcher

Job in Jersey City, Hudson County, New Jersey, 07390, USA
Listing for: NTT DATA North America
Full Time position
Listed on 2026-08-03
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), AI Evaluation, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 139872 - 209808 USD Yearly USD 139872.00 209808.00 YEAR
Job Description & How to Apply Below

Req : 382102

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us.

We are currently seeking a Applied AI Researcher to join our team in Jersey City, New Jersey (US-NJ), United States (US).

Applied AI Researcher

GenAI / NLP / Agentic AI / Applied Machine Learning

Role purpose Bridge advanced AI research and practical enterprise use cases by validating models, methods, and prototypes that can become production-grade AIRP solutions. The role focuses on measurable business value, rigorous experimentation, model behavior, and safe translation of research into banking-relevant applications.

Client-specific emphasis

  • Research must be grounded in enterprise business use cases, not generic AI experimentation.
  • Candidates should understand how model, retrieval, data, evaluation, latency, cost, and safety decisions affect production delivery on AIRP.
  • Cloud/AWS awareness is valuable because successful research outputs must be handed off to engineering teams building on AWS-hosted AIRP.

Primary Ownership

  • Applied research agenda for LLMs, NLP, RAG, evaluation, multimodal AI, and agentic workflows relevant to enterprise use cases.
  • Prototypes, experiments, benchmark design, model-selection recommendations, and production-readiness evidence.
  • Research-to-production handoff with AI engineering, AIRP platform, product, risk, and governance teams.

Key Responsibilities

  • Conduct applied research in LLMs, GenAI, NLP, information retrieval, multimodal AI, synthetic data, and agentic AI.
  • Design experiments to evaluate model performance, robustness, safety, scalability, interpretability, enterprise usefulness, and production feasibility.
  • Prototype AI solutions for KYC, credit underwriting, governance tracking, pitch book generation, Banker 360, Customer 360, deal library intelligence, financial crime quality, and sanctions screening.
  • Develop evaluation methodologies using golden datasets, adversarial testing, offline benchmarks, human review, business outcome metrics, and risk-specific acceptance criteria.
  • Assess prompt optimization, RAG, fine-tuning, instruction tuning, synthetic data generation, distillation, and model adaptation techniques.
  • Document model limitations, data assumptions, hallucination patterns, bias risks, performance boundaries, and control recommendations for regulated deployment.
  • Collaborate with engineers to convert prototypes into production-ready AIRP requirements, including latency, cost, observability, security, and AWS/cloud deployment considerations.
  • Track emerging AI research and translate relevant advances into practical recommendations for the enterprise.

Must-have candidate profile

  • Advanced degree preferred, usually MS or PhD in AI, ML, computer science, statistics, computational linguistics, mathematics, or related field.
  • Strong foundation in machine learning, deep learning, NLP, transformers, information retrieval, and generative AI.
  • Hands-on experience with LLMs, embeddings, RAG, model evaluation, and applied GenAI experimentation.
  • Python skills with PyTorch, Tensor Flow, Hugging Face, scikit-learn, or equivalent research frameworks.
  • Ability to design rigorous experiments and communicate findings to technical, product, business, risk, and governance stakeholders.
  • Ability to translate research results into production requirements suitable for an AWS-hosted enterprise platform.

Preferred Experience

  • Research or applied science experience in banking, finance, compliance, risk, legal, operations, financial crime, sanctions, or enterprise knowledge systems.
  • Experience with AWS Bedrock, Sage Maker, vector search, MLflow, Databricks, model evaluation tooling, or cloud-based experimentation environments.
  • Publications, patents, internal research contributions, open-source AI contributions, or prior research-to-production handoffs.
  • Familiarity with Responsible AI, model validation, privacy constraints, audit documentation, and regulated deployment environments.

NTT DATA provides a reasonable range of compensation for U.S.

-based positions. The starting pay range for this role will depend on the nature of the role offered and will either be [$139,872 - $209,808], or [$80-$100] if the…

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