Applied AI Researcher

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

• 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