AI/Machine Learning Engineer

Company: DataVisor
Location: Mountain View
Posted on: February 15, 2026

Job Description:

Job Description Job Description DataVisor 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 Summary We are hiring an AI/ML Engineer to serve as a technical architect for our Intelligence Layer and Data Consortium. This is a specialized engineering role—distinct from general web development—focused on building the high-scale "muscle" that powers our fraud intelligence. You will design and maintain distributed pipelines that ingest real-time signals from millions of users, and engineer backend systems that enable our Agentic Flow to "auto-tune" strategies. You will also play a key role in building agentic flows and AI applications using state-of-the-art, out-of-the-box large language models (LLMs) available on the market, in addition to helping build and deploy traditional machine learning models. Primary Responsibilities Consortium Data Engineering: Architect and maintain high-throughput data pipelines (using Spark, Kafka, or Flink) to ingest, process, and aggregate real-time signals—such as device fingerprints and behavioral biometrics—into our central intelligence graph. High-Scale System Design: Optimize distributed systems to support our global data network, ensuring the platform can handle 10,000 Transactions Per Second (TPS) with P99 latency under 150ms. Agentic Flow & AI Application Development: Build agentic flows and AI applications by leveraging state-of-the-art, out-of-the-box LLMs (e.g., OpenAI, Anthropic, Google) to enable natural language interaction, intelligent rule merging, and automated fraud strategy recommendations. Productionize ML Pipelines: Deploy and maintain pipelines for both Unsupervised (UML) and Supervised (SML) models, integrating them with our API to enable real-time scoring and decisioning. Privacy-First Architecture: Implement robust security measures, including tokenization and hashing, to ensure PII privacy and compliance across our shared intelligence network. Cross-Functional Collaboration: Work closely with Data Science, Product, Strategy, Delivery, and Engineering teams to develop, validate, and optimize machine learning models and AI-driven features. Requirements Qualifications Experience: 1–5 years of experience in Machine Learning Engineering, Data Engineering, or Backend Engineering. System Architecture: Proven ability to design distributed, cloud-native systems for high-throughput applications. Experience with AWS and containerization (Docker/Kubernetes) is critical. Big Data Tech: Strong hands-on experience with distributed data frameworks such as Spark, Kafka, or Flink. Coding Proficiency: Production-grade skills in Python and at least one compiled language (e.g., Java or C++). Preferred Qualifications Experience building or integrating LLM applications (LangChain, Vector DBs, RAG architectures). Background in real-time decision engines or stateful stream processing. Knowledge of fraud or risk domains is a plus, but not required. Benefits Base Salary Range: 130K - 200K Total Compensation: Includes Base Performance Bonus Equity Options. Benefits: Comprehensive medical, dental, and vision coverage. 401(k) retirement plan. Flexible Time Off (FTO) and paid holidays. Opportunities for R&D exploration and professional development. Regular team-building events and a collaborative, innovative culture.

Keywords: DataVisor, Rohnert Park , AI/Machine Learning Engineer, Engineering , Mountain View, California