Applied AI Researcher

Title: Applied AI Researcher

Location: Jersey City NJ(Hybrid)

Type: Contract

Description:

• Bridge advanced AI research and practical enterprise use cases by validating models methods and prototypes that can become production-grade solutions. The role focuses on measurable business value rigorous experimentation model behavior and safe translation of research into banking-relevant applications.
• Primary ownership
• Applied research agenda for LLMs NLP RAG evaluation multimodal AI and agentic workflows.
• Prototypes experiments benchmark design and model selection recommendations.
• Research-to-production handoff with AI engineering and platform 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 and enterprise usefulness.
• Prototype AI solutions for use cases such as document intelligence financial analysis compliance support knowledge retrieval and operational automation.
• Develop evaluation methodologies using golden datasets adversarial testing offline benchmarks human review and business outcome metrics.
• Assess prompt optimization RAG fine-tuning instruction tuning synthetic data generation distillation and model adaptation techniques.
• Collaborate with engineers to convert prototypes into production-ready systems with clear requirements limitations and acceptance criteria.
• Track emerging AI research and translate relevant advances into practical recommendations for the enterprise.
• Produce internal research papers technical notes implementation guides and thought-leadership materials.

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 TensorFlow Hugging Face scikit-learn or equivalent research frameworks.
• Ability to design rigorous experiments and communicate findings to technical and business stakeholders.
• Preferred experience
• Research or applied science experience in banking finance compliance risk legal operations or enterprise knowledge systems.
• Publications patents internal research contributions or open-source AI contributions.
• Familiarity with Responsible AI model validation privacy constraints and regulated deployment environments.
• Initial screening questions
• What research idea did you convert into a prototype or production capability
• How do you design an evaluation harness for an LLM-based banking use case
• How do you determine whether fine-tuning RAG or prompting is the right approach
• What failure modes did you discover and how did you mitigate them
• How do you communicate model limitations to non-research stakeholders