Principal AI/ML Research Engineer

Company Overview WEX is an innovative global commerce platform and payments technology company looking to forge the way in a rapidly changing environment, to simplify the business of doing business for customers, freeing them to spend more time, with less worry, on the things they love and care about. We are journeying to build a consistent world-class user experience across our products and services and leverage customer-focused innovations across all our strategic initiatives, including big data, AI, and Risk. Position Summary As a Principal AI/ML Research Engineer, this technical leader will drive applied AI research, novel model development, and algorithmic innovation across generative AI (GenAI), deep learning, and traditional machine learning. This technologist will lead the discovery, design, and prototyping of state-of-the-art architectures to solve complex, high-scale commerce and fintech challenges. For example, this work may include pioneering Transformer-based Payment Foundation Models (PFMs)-adapting self-attention mechanisms to large-scale tabular transaction data, user behavioral sequences, and multi-modal financial streams to produce universal embeddings that power a wide array of downstream commerce applications. This role bridges state-of-the-art academic/industry research with real-world production impact. You will closely partner with leaders in Data Engineering, Product, Security, Risk & Compliance, and Line of Business (LOB) technical teams to identify high-value opportunities, benchmark novel architectures (e.g., Tabular Transformers, LLMs, RAG, Reinforcement Learning), and transition experimental models into viable production pipelines. This Principal AI/ML Research Engineer will hold technical ownership of WEX s AI research strategy, model optimization, algorithmic rigor, and AI experimentation standards. The vision behind WEX s AI research is to transform multi-modal commerce and payment data into intelligent, predictive models that drive competitive advantage. This role reports to the VP of Data Lake and AI Engineering located in the San Jose, CA Bay Area, but can be located in Seattle, WA; Portland, ME; Boston, MA; or Chicago, IL. The ideal candidate is a hands-on technical leader with deep domain knowledge in applied AI/ML research, statistical modeling, and experimental design, combined with strong strategic vision and communication skills. Responsibilities • Self-Supervised Pre-Training & Fine-Tuning: Design self-supervised pre-training strategies (e.g., masked transaction prediction) on raw payment histories to generate multi-purpose user/entity embeddings, enabling efficient fine-tuning for fraud detection, credit risk, dispute prediction, and authorization optimization. • Payment Foundation Models & Transformers: Drive applied research in adapting Transformer architectures (encoder/decoder, self-attention mechanisms, and Tabular Transformers) to build enterprise-grade Payment Foundation Models (PFMs) tailored to transaction streams. • Research & Algorithmic Innovation: Lead applied research in AI/ML to solve high-impact business problems in fraud detection, risk scoring, predictive commerce, customer engagement, and automated decision-making. • Generative AI & Advanced Modeling: Spearhead research and prototyping in modern AI frameworks-including LLM fine-tuning, retrieval-augmented generation (RAG), agentic workflows, multi-modal systems, and Reinforcement Learning. • AI agent Feedback and Self-learning/improvement: lead development of effective framework and methodologies in auto AI agent feedback collection and agent self-learning and self-improvement. • Model Optimization: lead AI model optimization for performance, latency, and cost for Wex use cases, including developing model routers. • AI Agent Eval: lead the development of effective AI agent evaluation methodologies. • Proof-of-Concept to Production: Design and execute rigorous rapid-prototyping pipelines to validate new model architectures, feature representations, and algorithms before handing off to ML Engineering for scale-out. • Thought Leadership & Vision: Serve as a subject matter expert in state-of-the-art AI techniques, publishing research internally/externally where applicable, monitoring the academic landscape, and identifying emerging technologies to keep WEX at the forefront of AI innovation. • Cross-Functional Collaboration: Partner closely with Data Science, ML Engineering, Risk, Security, and Product teams to align research agendas with long-term business goals and ensure responsible AI deployment. • Model Benchmarking & Evaluation: Establish baseline benchmarks, mathematical validation protocols, explainability (XAI) frameworks, and performance evaluation metrics across predictive accuracy, latency, fairness, and bias reduction. • Responsible & Secure AI: Collaborate with Information Security, Compliance, and Governance teams to ensure AI models comply with data privacy regulations...