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DataVisorDA

AI/ML Engineer

DataVisor is an AI-powered fraud and risk management platform that utilizes unsupervised machine learning to help enterprises detect and prevent various digital threats in real-time.

DataVisor

Employee count: 51-200

Salary: 130k-200k USD

United States only

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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.

About the job

Apply before

Posted on

Job type

Full Time

Experience level

Senior

Salary

Salary: 130k-200k USD

Location requirements

Hiring timezones

United States +/- 0 hours

About DataVisor

Learn more about DataVisor and their company culture.

View company profile

DataVisor is a global leader in AI-powered fraud and risk management. Founded in 2013, the company provides an end-to-end Software-as-a-Service (SaaS) platform that leverages advanced artificial intelligence and machine learning capabilities to protect large consumer-facing enterprises and financial institutions from a wide array of digital threats. These threats include fraudulent transactions, spam, fake reviews, promotion abuse, fake application installs, identity theft, and money laundering. DataVisor's mission is to build and restore trust online by enabling organizations to proactively combat evolving fraud patterns in real-time.

The company's platform is distinguished by its patented unsupervised machine learning (UML) technology. This approach allows the system to identify new and unknown malicious actors and coordinated fraud rings without relying on historical labels or training data, which is crucial for staying ahead of sophisticated and rapidly changing attack vectors. DataVisor's solutions are designed to be data-agnostic, capable of ingesting and analyzing vast amounts of data from various sources to provide a holistic view of risk. The platform offers comprehensive capabilities including data orchestration, real-time feature computation, a flexible decision engine, and powerful case management tools. It is built to scale, handling high transaction volumes with low latency, making it suitable for some of the world's largest organizations. DataVisor serves a diverse range of industries, including financial services, banking, credit unions, fintech, e-commerce, social platforms, and digital payments, helping them to reduce fraud losses, improve operational efficiency, minimize customer friction, and ensure regulatory compliance.

Claim this profileDataVisor logoDA

DataVisor

Company size

51-200 employees

Founded in

2013

Chief executive officer

Yinglian Xie, Fang Yu

Employees live in

View company profile

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