Remotery

Principal AI/ML Research Engineer

Posted Aug 5

This is a fully remote position, open to applicants in Illinois, +3 more states.

📋 Description

• 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.


⛳️ Requirements

• 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.


🏝️ Benefits

• 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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