PhD Research Intern – Graph Learning, Agentic AI for Fraud Detection

🕒 March 28

🇺🇸 United States – Remote

💵 $40 - $90 / hour

👨‍🎓 Internship

⚪️ Entry-level

🚨 AML and Financial Crime

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Socure

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2012

🤖 Artificial Intelligence

🔐 Security

💸 Finance

💰 $450M Series E on 2021-11

Artificial Intelligence • Security • Finance

Socure is a leading platform for digital identity verification and trust. Utilizing advanced predictive analytics, artificial intelligence, and machine learning technologies, Socure leverages vast online and offline data intelligence including email, phone, address, IP, and device information to verify identities in real-time. Their solutions address challenges in onboarding, login authentication, account takeover prevention, and contact center operations. Socure's AI-powered platform excels in combating identity fraud, ensuring compliance, and enhancing user experiences across various industries such as financial services, eCommerce, online gaming, and crypto.

📋 Description

• Formulate and drive original research directions in graph learning for fraud detection, exploring architectures such as GNNs, graph transformers, and hybrid models • Design scalable approaches for dynamic, heterogeneous, and large-scale fraud graphs • Investigate agentic AI and LLM-augmented systems for automated risk reasoning, investigation workflows, and decision support • Develop robust learning techniques for adversarial and non-stationary environments • Conduct rigorous empirical evaluation on real-world, production-scale datasets • Translate research insights into practical system-level implications in collaboration with data scientists and engineers • Contribute to patent development and preparation of submissions to top-tier academic venues

🎯 Requirements

• Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related field • Strong research foundation in one or more of: • Graph representation learning (e.g., GNNs, graph transformers) • Transformer architectures and deep learning • LLMs and agentic AI systems • Adversarial, robust, or trustworthy machine learning • Demonstrated research capability (e.g., publications, preprints, or equivalent work) • Strong programming skills in Python • Experience with modern ML frameworks (e.g., PyTorch, TensorFlow, JAX) • Ability to independently scope and execute open-ended research problems • Publications at top-tier ML/AI/data mining conferences (e.g., NeurIPS, ICML, ICLR, KDD, WWW, WSDM, ACL) (Preferred Qualifications) • Experience scaling graph-based or transformer-based architectures to large datasets (Preferred Qualifications) • Familiarity with graph learning libraries (e.g., PyG, DGL) (Preferred Qualifications) • Experience working with noisy, highly imbalanced, or adversarial datasets (Preferred Qualifications)

🏖️ Benefits

• Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. • If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.