NTT DATA  Services

Applied AI Researcher

NTT DATA Services$104K — $182K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Advanced degree preferred (MS or PhD) in AI, ML, computer science, statistics, or related fields
  • At least 3 years of machine learning, deep learning, or NLP experience
  • 3+ years with LLMs, embeddings, and applied GenAI experimentation
  • Proficiency in Python and frameworks like PyTorch, TensorFlow
  • Experience conveying research findings to diverse stakeholders
  • Background in transitioning research to production on AWS platforms

Responsibilities

  • Conduct applied AI research focusing on LLMs, GenAI, NLP, and agentic AI
  • Design and execute experiments to assess model performance and feasibility
  • Prototype AI solutions for various financial applications like KYC and risk management
  • Develop evaluation methodologies using benchmarks and business metrics
  • Document model limitations and control recommendations for deployment
  • Collaborate with engineering teams for production read
  • Track AI research developments and adapt findings to enterprise needs

Benefits

  • Medical, dental, and vision insurance with employer contribution
  • Flexible spending or health savings account options
  • Life and AD&D insurance
  • Short and long-term disability coverage
  • Paid time off
  • 401k program with company match
  • Access to employee assistance programs
Full Job Description
Req ID: 382101

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

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.

Basic Qualifications:
  • Advanced degree preferred, usually MS or PhD in AI, ML, computer science, statistics, computational linguistics, mathematics, or related field.
  • 3+ years of experience in machine learning, deep learning, NLP, transformers, information retrieval, and generative AI.
  • 3+ years of experience with LLMs, embeddings, RAG, model evaluation, and applied GenAI experimentation.
  • 3+ years of experience in Python with PyTorch, TensorFlow, Hugging Face, scikit-learn, or equivalent research frameworks.
  • 3+ years of experience designing rigorous experiments and communicating findings to technical, product, business, risk, and governance stakeholders.
  • 3+ years of experience translating 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, SageMaker, 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 is $104,904 - $182,125 per year. Actual compensation will depend on a number of factors, including the candidate's relevant experience, technical skills, and other qualifications. This position may also be eligible for incentive compensation based on individual and/or company performance.

This position is eligible for company benefits including medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and AD&D insurance, short and long term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally-required benefits.

#LI-NorthAmerica, #DataFID

About NTT DATA Services

NTT DATA Corporation is a Japanese multinational information technology service and consulting company headquartered in Tokyo, Japan. It is partially-owned subsidiary of Nippon Telegraph and Telephone. Japan Telegraph and Telephone Public Corporation, a predecessor of NTT, started Data Communications business in 1967. NTT, following its privatization in 1985, spun off the Data Communications division as NTT DATA in 1988, which has now become the largest of the IT Services companies headquartered in Japan.
Learn more about NTT DATA Services
Size
151,991 employees
Industry
Founded
1988
NASDAQ

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