Principal AI/ML Research Engineer

Role Description

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 role bridges state-of-the-art academic/industry research with real-world production impact.

• Design self-supervised pre-training strategies on raw payment histories to generate multi-purpose user/entity embeddings.
• Drive applied research in adapting Transformer architectures to build enterprise-grade Payment Foundation Models (PFMs) tailored to transaction streams.
• 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.
• Spearhead research and prototyping in modern AI frameworks, including LLM fine-tuning, retrieval-augmented generation (RAG), agentic workflows, multi-modal systems, and Reinforcement Learning.
• Lead development of effective framework and methodologies in auto AI agent feedback collection and agent self-learning and self-improvement.
• Lead AI model optimization for performance, latency, and cost for WEX use cases, including developing model routers.
• Lead the development of effective AI agent evaluation methodologies.
• Design and execute rigorous rapid-prototyping pipelines to validate new model architectures, feature representations, and algorithms.
• Serve as a subject matter expert in state-of-the-art AI techniques, publishing research internally/externally where applicable.
• Partner closely with Data Science, ML Engineering, Risk, Security, and Product teams to align research agendas with long-term business goals.
• Establish baseline benchmarks, mathematical validation protocols, explainability (XAI) frameworks, and performance evaluation metrics.
• Collaborate with Information Security, Compliance, and Governance teams to ensure AI models comply with data privacy regulations.
• Set a high standard for scientific research and engineering rigor within the team.
• Define, prioritize, and execute WEX’s AI research roadmap, balancing foundational research with near-term business impact.

Qualifications

• 12+ years of experience in software/ML engineering, with 5+ years dedicated to applied AI/ML research.
• Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field preferred.
• Deep expertise applying Transformer models and self-supervised pre-training techniques to financial/transactional datasets.
• Proven expertise in modern AI paradigms—Transformers, LLM pre-training/fine-tuning, RAG architectures, prompt engineering, and Reinforcement Learning.
• Strong theoretical foundation and hands-on experience in supervised/unsupervised learning, time-series forecasting, and anomaly detection.
• Expert proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, JAX).
• Strong understanding of distributed training/inference frameworks such as Ray, DeepSpeed, Megatron, or Spark.
• Hands-on experience with cloud environments (AWS/Azure) and ML platforms like SageMaker, MLflow, and Databricks.
• Demonstrated ability to translate complex academic literature into production-grade prototypes.
• Experience applying AI/ML algorithms to payments, fintech, risk management, fraud detection, or transactional big data is a major plus.
• Exceptional capability to explain highly technical research concepts to non-technical executive leadership.

Requirements

• Possesses a relentless drive to stay ahead of the AI curve, continuously learning and experimenting with cutting-edge techniques.
• Bridges the gap between research curiosity and business execution with humility, empathy, and transparent communication.
• Thrives in a fast-paced environment, comfortably pushing boundaries and challenging the status quo.
• Demonstrates an uncompromising commitment to AI fairness, safety, explainability, and regulatory compliance.

Benefits

• Health, dental, and vision insurances.
• Retirement savings plan.
• Paid time off.
• Health savings account and flexible spending accounts.
• Life insurance and disability insurance.
• Tuition reimbursement.
• Quarterly or annual bonus based on role and applicable plan.