Principal AI/ML Research Engineer

WEX

Principal AI/ML Research Engineer developing Payment Foundation Models and generative AI for WEX’s global commerce and payments platform. Leading research from novel architectures through production-ready fintech applications.

Posted 8/5/2026full-timeRemote • Illinois, Maine, Massachusetts, Washington • 🇺🇸 United StatesLead💰 $250,300 - $289,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in applied AI and machine learning, particularly in Transformer models and self-supervised learning, with a strong focus on developing innovative algorithms for fintech and commerce applications. Proven ability to lead research initiatives, optimize AI models, and ensure responsible AI deployment aligned with ethical standards and privacy regulations.

Highest-signal resume keywords

Applied AI/ML ResearchTransformer Model DevelopmentSelf-Supervised LearningPython ProficiencyFintech Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning EngineeringAlgorithm DevelopmentModel Architecture DesignReinforcement LearningAnomaly DetectionTime-Series ForecastingGraph AlgorithmsLLM Fine-TuningSelf-Attention MechanismsDeep Learning Frameworks

Soft Skills

Technical GuidanceMentorshipCross-Functional CommunicationResearch Concept Explanation

Tools & Technologies

PyTorchTensorFlowJAXAWSAzureSageMakerMLflowDatabricksRayDeepSpeed

Certifications & Qualifications

Master’s or Ph.D. in Computer ScienceMachine LearningStatisticsMathematics

Industry Keywords

FintechFraud DetectionRisk ManagementTransactional Big DataPayments

Tech Stack

Tools & technologies

AWSAzureJavaPythonPyTorchRaySparkTensorflow

About the role

Key responsibilities & impact

Drive applied AI research, novel model development, and algorithmic innovation across generative AI, deep learning, and traditional machine learning
Discover, design, and prototype state-of-the-art architectures for large-scale commerce and fintech challenges
Design self-supervised pre-training strategies on payment histories to generate reusable user and entity embeddings
Adapt Transformer architectures and self-attention mechanisms to build enterprise-grade Payment Foundation Models
Lead research in fraud detection, risk scoring, predictive commerce, customer engagement, and automated decision-making
Research and prototype LLM fine-tuning, RAG, agentic workflows, multi-modal systems, and reinforcement learning
Develop AI-agent feedback, self-learning, self-improvement, and evaluation methodologies
Optimize AI models for performance, latency, and cost, including model routers
Design rapid-prototyping pipelines to validate models and algorithms before transition to ML Engineering
Serve as a subject matter expert, monitor academic research, and identify emerging technologies
Partner with Data Science, ML Engineering, Risk, Security, Product, Compliance, and Governance teams
Establish benchmarks, mathematical validation protocols, explainability frameworks, and evaluation metrics
Ensure responsible and secure AI deployment aligned with privacy regulations, ethical principles, and security standards
Provide technical guidance, code and mathematics reviews, and mentorship
Define, prioritize, and execute WEX’s AI research roadmap and OKRs

Requirements

What you’ll need

12+ years of experience in software/ML engineering
5+ years dedicated to applied AI/ML research, model architecture design, novel algorithm development at scale, AI application development, and AI agent development
Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field preferred, or equivalent qualifications
Deep expertise applying Transformer models, self-attention mechanisms, and self-supervised pre-training to sequential, time-series, or tabular financial/transactional datasets
Proven expertise in Transformers, LLM pre-training/fine-tuning, LoRA, PEFT, RAG architectures, prompt engineering, Diffusion, or Reinforcement Learning/RLHF
Strong theoretical foundation and hands-on experience in supervised and unsupervised learning, time-series forecasting, anomaly detection, and graph algorithms
Expert proficiency in Python and deep learning frameworks including PyTorch, TensorFlow, and JAX
Experience in C++ or Java for performance-critical ML components is a plus
Strong understanding of Ray, DeepSpeed, Megatron, or Spark
Hands-on experience with AWS or Azure
Experience with SageMaker, MLflow, Databricks, or vector databases such as LanceDB, Pinecone, Qdrant, or Milvus
Ability to translate academic literature into production-grade prototypes
Publications in top AI/ML venues or open-source contributions highly desirable
Experience in payments, fintech, risk management, fraud detection, or transactional big data is a major plus
Exceptional ability to explain technical research concepts and mathematical models to executives and cross-functional partners

Benefits

Comp & perks

Health, dental and vision insurances
Retirement savings plan
Paid time off
Health savings account
Flexible spending accounts
Life insurance
Disability insurance
Tuition reimbursement
Quarterly or annual bonus eligibility for non-sales roles
Reasonable accommodation support
Equal opportunity and diversity and inclusion commitment
Drug-free workplace