AI Research Scientist

• Monitor, evaluate, and experiment with emerging AI technologies, research breakthroughs, and industry trends, with particular emphasis on generative AI, large language models (LLMs), multimodal AI, and agentic AI systems.
• Identify opportunities to apply advanced AI techniques to complex business problems across financial services.
• Conduct original AI research and exploratory investigations to assess the feasibility and value of novel approaches.
• Develop hypotheses, design experiments, evaluate results, and communicate findings to technical and business stakeholders.
• Contribute to patents, technical publications, whitepapers, prototypes, and innovation initiatives.
• Rapidly transform research concepts into working prototypes and proof-of-concepts.
• Design, develop, and validate AI solutions across the full lifecycle, from data preparation and modeling through deployment and monitoring.
• Build experimental and production-ready solutions using modern AI/ML tools, frameworks, and cloud platforms.
• Apply best practices in model evaluation, benchmarking, explainability, security, and responsible AI.
• Develop solutions leveraging foundation models, generative AI, retrieval-augmented generation (RAG), fine-tuning techniques, and agentic workflows.
• Partner with software engineers, platform teams, product managers, and business stakeholders to transition successful prototypes into production environments.
• Share knowledge and provide technical guidance to peers and junior team members.

• Bachelor's degree in a quantitative field such as statistics, computer science, engineering or applied mathematics, or equivalent work experience
• Eight or more years of relevant experience
• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Computational Linguistics, or a related field strongly preferred.
• Deep expertise in machine learning, deep learning, neural networks, transformer architectures, and foundation models.
• Experience with generative AI technologies, including LLMs, fine-tuning, RAG systems, model evaluation, and inference optimization.
• Experience building and evaluating agentic AI systems, multi-agent workflows, AI orchestration frameworks, and autonomous decision-making architectures.
• Hands-on experience with PyTorch, Hugging Face, Lang Chain, Lang Graph, or equivalent AI ecosystems.
• Demonstrated record of innovation through publications, patents, open-source contributions, conference presentations, or impactful AI solution delivery.
• Experience developing AI solutions within highly regulated industries such as financial services, healthcare, insurance, or telecommunications.
• Strong communication skills and the ability to translate complex AI concepts into actionable business outcomes.

Demonstrates expertise in developing and validating AI solutions, particularly in generative AI and large language models, while effectively communicating complex concepts to stakeholders. Proven ability to innovate through research, patents, and publications within regulated industries.

• Machine Learning Expertise
• Generative AI Technologies
• Deep Learning and Neural Networks
• AI Solution Development
• Strong Communication Skills

• Machine Learning
• Deep Learning
• Neural Networks
• Transformer Architectures
• Generative AI
• Fine-Tuning Techniques
• Model Evaluation
• Inference Optimization
• AI Orchestration Frameworks
• Autonomous Decision-Making

• Strong Communication Skills

• Ph.D. in Computer Science
• Bachelor's Degree in Quantitative Field

• Financial Services
• Healthcare
• Insurance
• Telecommunications
• Regulated Industries

• Py Torch
• Hugging Face
• Lang Chain
• Lang Graph
• AI/ML Tools
• Cloud Platforms