Applied AI Researcher

About the role

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.

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.

Requirements

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, TensorFlow, 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.

Qualifications

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.

Skills

Must-have candidate profile includes advanced degree, strong foundation in machine learning, hands-on experience with LLMs, and ability to design rigorous experiments and communicate findings. Preferred experience includes research or applied science experience in banking, finance, compliance, risk, legal, operations, financial crime, sanctions, or enterprise knowledge systems. Experience with AWS, publications, patents, and open-source AI contributions are also valued.

Benefits

Negotiable starting salary range based on experience. Eligible for incentive compensation based on individual and/or company performance. Company benefits include medical, dental, and vision insurance, 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.

Pay

$139,872 - $209,808, or [$80-$100] if the role is hired as a temporary position. Actual compensation will depend on a number of factors, including the candidate’s relevant experience, technical skills, and other qualifications.

Schedule

This position may also be eligible for incentive compensation based on individual and/or company performance. If the position offered in temporary, the position will not be eligible for incentive compensation.