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Applied Ai Researcher

  • Applied Ai Researcher job type Posted on: Oct 15, 2026
  • Applied Ai Researcher experience level United Software Group Inc
  • Applied Ai Researcher employment type Jersey City, New Jersey
  • Applied Ai Researcher employment type Onsite
  • Applied Ai Researcher salary CTC

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Job Title :

Applied Ai Researcher

Job Type :

Contract

Job Location :

Jersey City New Jersey United States

Remote :

No

Jobcon Logo Job Description :

Job Title: Applied AI Researcher (GenAI, NLP & Agentic AI)

Location: Jersey City, NJ. Onsite 4 days a week; a face-to-face interview at the client's Jersey City location is mandatory.

Employment Type: Contract

Client: Large financial services client

About the Role
We're looking for an Applied AI Researcher to bridge advanced AI research and real enterprise use cases at a large banking client. You'll validate models, methods, and prototypes that can become production-grade solutions, with a focus on measurable business value, rigorous experimentation, and safe translation of research into regulated banking applications.

Key Responsibilities

  • Conduct applied research in LLMs, GenAI, NLP, information retrieval, multimodal AI, synthetic data, and agentic AI
  • Design experiments to evaluate performance, robustness, safety, scalability, interpretability, and production feasibility
  • Prototype AI solutions for financial services use cases such as KYC, credit underwriting, customer 360 views, financial crime, and sanctions screening
  • Build evaluation methods using golden datasets, adversarial testing, offline benchmarks, human review, and risk-specific acceptance criteria
  • Assess prompt optimization, RAG, fine-tuning, instruction tuning, distillation, and other model adaptation techniques
  • Document model limitations, hallucination patterns, bias risks, and control recommendations for regulated deployment
  • Work with engineers to turn prototypes into production requirements covering latency, cost, observability, security, and AWS deployment
  • Track emerging AI research and turn it into practical recommendations

Required Skills & Experience

  • MS or PhD preferred in AI, ML, computer science, statistics, computational linguistics, mathematics, or a 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 with PyTorch, TensorFlow, Hugging Face, scikit-learn, or equivalent
  • Ability to design rigorous experiments and explain findings to technical, product, business, risk, and governance stakeholders
  • Ability to turn research results into production requirements for an AWS-hosted enterprise platform

Preferred

  • Applied science or research experience in banking, finance, compliance, risk, legal, or financial crime
  • Experience with AWS Bedrock, SageMaker, vector search, MLflow, Databricks, or cloud experimentation environments
  • Publications, patents, open-source AI contributions, or research-to-production handoffs
  • Familiarity with Responsible AI, model validation, privacy constraints, and regulated deployment

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Jobcon Logo Position Details

Posted:

Oct 15, 2026

Reference Number:

85889-2308

Employment:

CTC

City:

Jersey City

Job Origin:

CIEPAL_ORGANIC_FEED

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Job Title: Applied AI Researcher (GenAI, NLP & Agentic AI)

Location: Jersey City, NJ. Onsite 4 days a week; a face-to-face interview at the client's Jersey City location is mandatory.

Employment Type: Contract

Client: Large financial services client

About the Role
We're looking for an Applied AI Researcher to bridge advanced AI research and real enterprise use cases at a large banking client. You'll validate models, methods, and prototypes that can become production-grade solutions, with a focus on measurable business value, rigorous experimentation, and safe translation of research into regulated banking applications.

Key Responsibilities

  • Conduct applied research in LLMs, GenAI, NLP, information retrieval, multimodal AI, synthetic data, and agentic AI
  • Design experiments to evaluate performance, robustness, safety, scalability, interpretability, and production feasibility
  • Prototype AI solutions for financial services use cases such as KYC, credit underwriting, customer 360 views, financial crime, and sanctions screening
  • Build evaluation methods using golden datasets, adversarial testing, offline benchmarks, human review, and risk-specific acceptance criteria
  • Assess prompt optimization, RAG, fine-tuning, instruction tuning, distillation, and other model adaptation techniques
  • Document model limitations, hallucination patterns, bias risks, and control recommendations for regulated deployment
  • Work with engineers to turn prototypes into production requirements covering latency, cost, observability, security, and AWS deployment
  • Track emerging AI research and turn it into practical recommendations

Required Skills & Experience

  • MS or PhD preferred in AI, ML, computer science, statistics, computational linguistics, mathematics, or a 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 with PyTorch, TensorFlow, Hugging Face, scikit-learn, or equivalent
  • Ability to design rigorous experiments and explain findings to technical, product, business, risk, and governance stakeholders
  • Ability to turn research results into production requirements for an AWS-hosted enterprise platform

Preferred

  • Applied science or research experience in banking, finance, compliance, risk, legal, or financial crime
  • Experience with AWS Bedrock, SageMaker, vector search, MLflow, Databricks, or cloud experimentation environments
  • Publications, patents, open-source AI contributions, or research-to-production handoffs
  • Familiarity with Responsible AI, model validation, privacy constraints, and regulated deployment

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