DataVisor

About the Company

DataVisor is the world's leading fraud and risk management platform that enables organizations to respond to fast-evolving fraud attacks and mitigate risks as they happen in real time. Its comprehensive solution suite combines patented machine learning technology with native device intelligence and a powerful decision engine to provide protection for the entire customer lifecycle across industries and use cases. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Listed Jobs

Company Name

DataVisor

Job Title

AI/Machine Learning Engineering Intern (MS/Ph.D. New Grad)

Job Description

**Job Title** AI/Machine Learning Engineering Intern (MS/Ph.D. New Grad) **Role Summary** Internship focused on building and scaling real‑time AI systems for fraud detection. Collaborate with engineers and data scientists to develop data pipelines, distributed backend services, and ML inference pipelines, with exposure to large language models and agentic workflows. **Expectations** - Recently graduated or currently completing an MS or Ph.D. in Computer Science, Machine Learning, AI, Data Science, or related field. - Strong motivation to learn production‑scale AI engineering. - Ability to tackle complex technical problems and grow through mentorship. **Key Responsibilities** - Build and maintain high‑throughput data pipelines using Spark, Kafka, or Flink. - Process and aggregate real‑time signals (device fingerprints, behavioral data) for shared intelligence. - Design and optimize distributed backend systems for low‑latency, high‑volume decisioning. - Develop AI applications and agentic workflows with LLMs (OpenAI, Anthropic, Google). - Deploy, monitor, and integrate supervised and unsupervised ML models into real‑time scoring APIs. - Implement privacy‑first design practices (tokenization, hashing). - Collaborate cross‑functionally with Data Science, Product, and Engineering teams to test models and ship features. **Required Skills** - Proficient in Python programming. - Familiarity with distributed systems, machine learning, data engineering, or backend development. - Experience or coursework in big data frameworks (Spark, Kafka, Flink) a plus. - Understanding of core ML concepts (supervised and unsupervised learning). **Required Education & Certifications** - MS or Ph.D. in Computer Science, Machine Learning, AI, Data Science, or related field (current or recently completed).

Mountain view, United states

Hybrid

Fresher

22-12-2025

Company Name

DataVisor

Job Title

Machine Learning Engineer - Fraud Detection

Job Description

**Job Title:** Machine Learning Engineer – Fraud Detection **Role Summary:** Design, develop, and deploy large‑scale unsupervised machine‑learning models that detect fraudulent activity across financial transactions, mobile acquisition, social networks, and commerce. Work with billions of events, collaborate with data scientists and infrastructure engineers, and continuously improve detection accuracy and system performance. **Expectations:** - 2+ years of professional software development in Java or C++. - Strong grasp of data structures, algorithms, and writing optimized code. - 1+ year experience with web back‑end services or big‑data platforms (Hadoop, MapReduce, Spark). - Exposure to machine‑learning or data‑science workflows (preferred). - Ability to handle high‑volume data pipelines and contribute to model enhancements. - Experience in anti‑fraud modeling within the financial sector is a plus. **Key Responsibilities:** - Build and maintain fraud‑detection pipelines on Hadoop/Spark clusters. - Implement, test, and optimize unsupervised ML algorithms for anomaly detection. - Integrate models into production back‑end services and APIs. - Collaborate with data scientists to translate research prototypes into scalable solutions. - Monitor model performance, conduct root‑cause analyses, and iterate improvements. - Write clean, well‑documented, and version‑controlled code adhering to best practices. **Required Skills:** - Java or C++ programming (expert level). - Proficient in core data structures and algorithm design. - Experience with web backend development or big‑data frameworks (Hadoop, MapReduce, Spark). - Familiarity with machine‑learning concepts and tools (Python/R, scikit‑learn, TensorFlow, etc.). - Strong problem‑solving abilities and comfort with large‑scale data processing. - Linux/Unix environment, Git or other source‑control systems. **Required Education & Certifications:** - Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related quantitative field (required). - Master’s or PhD in a relevant discipline (preferred). - Relevant certifications (e.g., AWS Certified Big Data, Google Cloud Professional Data Engineer) are optional but advantageous.

Mountain view, United states

On site

Junior

15-01-2026