AI/Machine Learning Engineering - Intern

About DataVisorDataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!Role SummaryWe are seeking highly motivated, soon-to-graduate MS or Ph.D. students in Computer Science, Machine Learning, Data Science, or related fields to join us as AI / ML Engineering Interns.This internship is ideal for candidates who are eager to learn how large-scale AI systems are built and deployed in production. You will work closely with experienced engineers and data scientists to help build the Intelligence Layer and Data Consortium that power DataVisor's real-time fraud detection platform.This internship focuses on distributed systems, data pipelines, machine learning infrastructure, and applied AI, including exposure to agentic flows and large language models (LLMs).What You'll DoData Engineering & PipelinesAssist in building and maintaining high-throughput data pipelines using technologies such as Spark, Kafka, or FlinkHelp process and aggregate real-time signals (e.g., device fingerprints, behavioral data) into shared intelligence systemsDistributed Systems & ScalabilityLearn to design and optimize backend systems that support large-scale, real-time decisioningContribute to improving system performance, reliability, and latency under high transaction volumesAI Applications & Agentic FlowsSupport the development of AI applications and agentic workflows using state-of-the-art LLMs (e.g., OpenAI, Anthropic, Google)Experiment with natural language interfaces, intelligent rule suggestions, and automated strategy generationMachine Learning PipelinesHelp deploy and monitor pipelines for unsupervised and supervised ML modelsAssist with integrating models into real-time scoring APIs and decision enginesPrivacy & SecurityLearn best practices for privacy-first system design, including tokenization and hashing to protect sensitive dataCross-Functional CollaborationWork alongside Data Science, Product, and Engineering teams to test ideas, validate models, and ship production featuresCurrent MS or Ph.D. students majoring in Computer Science, Machine Learning, AI, Data Science, or a related fieldPassionate about learning how real-world AI systems are built at scaleComfortable working with complex technical problems and eager to grow through mentorshipStrong programming skills in PythonFamiliarity with at least one of the following: distributed systems, machine learning, data engineering, or backend developmentAcademic or project experience with big data frameworks (Spark, Kafka, Flink) is a plusUnderstanding of core ML concepts (supervised / unsupervised learning)Preferred (Nice-to-Have)Coursework or project experience with:LLMs, RAG architectures, LangChain, or vector databasesCloud platforms (AWS) and containers (Docker)Stream processing or real-time systemsInterest in fraud, risk, or security domains (not required)Hands-on experience working on production-scale AI systemsMentorship from senior engineers and data scientistsExposure to cutting-edge agentic AI and LLM applicationsOpportunity for full-time conversion based on performance and business needsComp Range, $25 - $70/hour