AI/Machine Learning Engineering Intern, DataVisor

MS/Ph.D. New Grad

Salary not provided

Comp Range: $25 - $70/hour

AWS

Docker

Python

Kafka

Spark

Flink

San Francisco Bay Area

Office located in Mountain View, CA

ML-powered fraud detection

Be an early applicant

ML-powered fraud detection

101-200 employees

B2BArtificial IntelligenceSecurityEnterpriseBig dataDeep TechAnalyticsMachine LearningSaaSAPICyber SecurityIdentityFraud

Be an early applicant

Salary not provided

Comp Range: $25 - $70/hour

AWS

Docker

Python

Kafka

Spark

Flink

San Francisco Bay Area

Office located in Mountain View, CA

101-200 employees

B2BArtificial IntelligenceSecurityEnterpriseBig dataDeep TechAnalyticsMachine LearningSaaSAPICyber SecurityIdentityFraud

Company mission

To deliver the world’s most sophisticated AI-powered solutions to keep companies and their customers safe from fraud and abuse.

Job

Company

Role

Who you are

This internship is ideal for candidates who are eager to learn how large-scale AI systems are built and deployed in production
Recently graduated or currently completing an MS or Ph.D. in Computer Science, Machine Learning, AI, Data Science, or a related field
Passionate about learning how real-world AI systems are built at scale
Comfortable working with complex technical problems and eager to grow through mentorship
Strong programming skills in Python
Familiarity with at least one of the following: distributed systems, machine learning, data engineering, or backend development
Academic or project experience with big data frameworks (Spark, Kafka, Flink) is a plus
Understanding of core ML concepts (supervised / unsupervised learning)

Desirable

Coursework or project experience with:
LLMs, RAG architectures, LangChain, or vector databases
Cloud platforms (AWS) and containers (Docker)
Stream processing or real-time systems
Interest in fraud, risk, or security domains (not required)

What the job involves

We are seeking highly motivated, newly graduated or 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
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)
Assist in building and maintaining high-throughput data pipelines using technologies such as Spark, Kafka, or Flink
Help process and aggregate real-time signals (e.g., device fingerprints, behavioral data) into shared intelligence systems
Learn to design and optimize backend systems that support large-scale, real-time decisioning
Contribute to improving system performance, reliability, and latency under high transaction volumes
Support 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 generation
Help deploy and monitor pipelines for unsupervised and supervised ML models
Assist with integrating models into real-time scoring APIs and decision engines
Learn best practices for privacy-first system design, including tokenization and hashing to protect sensitive data
Work alongside Data Science, Product, and Engineering teams to test ideas, validate models, and ship production features
Hands-on experience working on production-scale AI systems
Mentorship from senior engineers and data scientists
Exposure to cutting-edge agentic AI and LLM applications
Opportunity for full-time conversion based on performance and business needs

Our take

As the use of online shopping and banking continues to rise, so too does the opportunity for fraud, with criminals exploiting the gaps in defences that come with an increasingly novel digital environment. DataVisor provides the leading fraud detection solution that leverages machine learning to identify threats, to overcome the security gap caused by the speed at which today’s digital fraudsters evolve.

Traditional fraud solutions have not been designed to handle digital data, and they are especially ill-equipped to deal with quickly changing environments. By employing advanced ML, DataVisor can identify the patterns which allude to fraudulent behaviour, allowing organisations to respond immediately and prevent losses before they happen. Another problem with some systems has been that, in the name of security, they might delay ultimately good customers from accessing services. With DataVisor this becomes a non-issue, as the pattern of a non-malicious user can also be identified with speed.

DataVisor has seen considerable investment - that will fuel its continued expansion across the globe - and has an impressive list of customers. The company has also made several partnerships that will act towards strengthening its product offering. For example, it is extending its analytics and fraud detection through partnership with Equifax, by gaining access to its rich consumer identity data.

Steph

Company Specialist at Welcome to the Jungle

Insights

Led by a woman

Glassdoor (4.4)

Company

Funding (last 2 of 3 rounds)

Dec 2022

$40m

LATE VC

Feb 2018

$40m

SERIES C

Total funding: $94.5m

Company benefits

Stock Options
Commuter Passes
Paid Time Off
Catered Lunch and Dinner
Team and Company Outings

Company HQ

Mountain View, CA

Leadership

Yinglian Xie

(CEO)

Extensive experience in security and AI. Previously a Senior Researcher at Microsoft Research.

Fang Yu

(CPO)

Former Senior Researcher at Microsoft Research, with vast experience in big-data algorithms.

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