Staff Applied Scientist

📋 Description

• • Design, develop, and deploy generative AI and agentic AI systems to power identity verification, fraud prevention, and risk intelligence solutions for enterprise clients.
• • Lead end-to-end development of deep learning models including large language models (LLMs), graph neural networks, and reinforcement learning architectures optimized for real-world production use.
• • Collaborate with cross-functional teams of engineers, product leaders, and data scientists to translate ambiguous research concepts into scalable, reliable AI products used at national and global scales.
• • Design and implement agentic AI systems with tool usage, function calling, planning, multi-agent orchestration, and retrieval-augmented generation (RAG) capabilities for dynamic decision-making in identity and risk contexts.
• • Pre-train and fine-tune foundational LLMs using supervised fine-tuning, RLHF, DPO, LoRA, PEFT, and model distillation techniques to enhance performance and efficiency.
• • Build and optimize AI/ML pipelines leveraging PyTorch, TensorFlow, or JAX, with strong proficiency in Python and C++ for high-performance model development and deployment.
• • Architect and deploy scalable AI solutions integrated into production systems supporting real-time identification, asset linking, and relationship mapping for compliance and due diligence workflows.
• • Drive independent research initiatives from problem framing and prototyping through productionization and post-launch iteration, owning outcomes with minimal supervision.
• • Evaluate agent behavior and model performance in live environments using rigorous metrics and iterative feedback loops to ensure accuracy, reliability, and regulatory compliance.
• • Apply transformer architectures and NLP techniques specifically to generative and agentic AI applications within identity intelligence and fraud detection domains.
• • Work on high-impact systems that reduce societal costs by minimizing fraud, enhancing safety, and enabling frictionless commerce through advanced AI-driven identity intelligence.
• • Maintain deep technical engagement with cutting-edge research, rapidly translating academic advances into functional prototypes and shipped products within agile timelines.
• • Partner with engineering teams to ensure AI models are production-ready, monitored, versioned, and scalable across distributed infrastructure.
• • Contribute to the evolution of the company’s AI roadmap by identifying new opportunities in identity graph modeling, behavioral risk prediction, and autonomous verification agents.
• • Document technical designs, model performance, and deployment processes to ensure knowledge sharing and reproducibility across the AI team.
• • Participate in internal and external knowledge sharing, including presentations, code reviews, and technical mentoring of junior scientists and engineers.
• • Maintain awareness of regulatory requirements in identity verification and financial compliance to ensure AI solutions meet legal and ethical standards.
• • Contribute to team innovation through experimentation, failure analysis, and continuous learning in a fast-paced environment that values creativity and technical rigor.