
Principal AI/ML Research Engineer
Posted Aug 5

Posted Aug 5
This is a fully remote position, open to applicants in Illinois, +3 more states.
• Lead research in applied AI, innovative model creation, and algorithm development focusing on generative AI, deep learning, and traditional machine learning.
• Identify, design, and prototype cutting-edge architectures to address large-scale challenges in commerce and fintech.
• Create self-supervised pre-training strategies utilizing payment histories to develop reusable user and entity embeddings.
• Modify Transformer architectures and self-attention mechanisms to construct enterprise-level Payment Foundation Models.
• Conduct research in areas such as fraud detection, risk scoring, predictive commerce, customer engagement, and automated decision-making.
• Investigate and prototype fine-tuning of LLMs, RAG, agentic workflows, multi-modal systems, and reinforcement learning techniques.
• Develop methodologies for AI-agent feedback, self-learning, self-improvement, and evaluation processes.
• Enhance AI models for efficiency, latency, and cost-effectiveness, including the integration of model routers.
• Create rapid-prototyping pipelines to test models and algorithms prior to their transition to ML Engineering.
• Act as a subject matter expert, keeping abreast of academic research and identifying emerging technologies.
• Collaborate with teams in Data Science, ML Engineering, Risk, Security, Product, Compliance, and Governance.
• Set benchmarks, mathematical validation protocols, explainability frameworks, and evaluation metrics.
• Ensure that AI deployment is responsible and secure, adhering to privacy regulations, ethical standards, and security protocols.
• Offer technical guidance, conduct code and mathematical reviews, and provide mentorship.
• Define, prioritize, and implement WEX’s AI research roadmap and OKRs.
• Over 12 years of experience in software and ML engineering.
• At least 5 years focused on applied AI/ML research, model architecture design, large-scale algorithm development, AI application development, and AI agent development.
• A Master’s or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field is preferred, or equivalent qualifications.
• Extensive expertise in applying Transformer models, self-attention mechanisms, and self-supervised pre-training to financial or transactional datasets across various formats.
• Demonstrated proficiency in Transformers, LLM pre-training/fine-tuning, LoRA, PEFT, RAG architectures, prompt engineering, Diffusion, and Reinforcement Learning/RLHF.
• Strong theoretical background and practical experience in supervised and unsupervised learning, time-series forecasting, anomaly detection, and graph algorithms.
• Advanced proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, and JAX.
• Familiarity with C++ or Java for high-performance ML components is advantageous.
• Solid understanding of Ray, DeepSpeed, Megatron, or Spark.
• Practical experience with AWS or Azure.
• Experience using SageMaker, MLflow, Databricks, or vector databases like LanceDB, Pinecone, Qdrant, or Milvus.
• Capability to translate academic research into production-quality prototypes.
• Publications in leading AI/ML conferences or contributions to open-source projects are highly desirable.
• Experience in payments, fintech, risk management, fraud detection, or large-scale transactional data is a significant plus.
• Exceptional ability to convey complex technical research concepts and mathematical models to executives and cross-functional teams.
• Health, dental, and vision insurance.
• Retirement savings plan.
• Paid time off.
• Health savings account.
• Flexible spending accounts.
• Life insurance.
• Disability insurance.
• Tuition reimbursement.
• Eligibility for quarterly or annual bonuses for non-sales positions.
• Support for reasonable accommodations.
• Commitment to equal opportunity, diversity, and inclusion.
• Drug-free workplace.
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