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Required Part-Time Software Engineering PhD Intern, 2027
Please complete your application before 23rd October 2026. We encourage you to apply as early as possible as we review applications on a rolling basis.
This internship is intended for students in their penultimate/final year of education in an accredited full-time PhD degree program in Israel. Participation in the internship program requires that you are located in Israel for this role for the duration of the internship program. Interns will be required to be available to work part-time (minimum 2 days a week, maximum 4 days a week) alongside your studies for a minimum of 26 weeks starting early 2027 (starting in March, April or May) for the duration of the program. Individuals applying for this position will not be eligible for immigration sponsorship.
About the job
As a Software Engineering intern, you will work on a specific project critical to our needs. As a key member of a versatile team, you will work on a specific project critical to our needs. We need our engineers to be versatile, and enthusiastic in addressing problems as we continue to push technology forward. You will design, test, deploy and maintain software solutions as you grow and evolve during your internship.
We are an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. Engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Ads to Chrome, Android to YouTube, social to local, our engineers are changing the world one technological achievement after another.
Responsibilities
Research, conceive and develop software applications to extend and improve on our product offering.
Contribute to a wide variety of projects using natural language processing, artificial intelligence, data compression, machine learning, and search technologies
Collaborate on scalability issues involing access to data and information.
Utilise exposure to large-scale production software troubleshooting.
Help maintain mission critical services.

As we scale and evolve our fully automated fraud prevention strategies, we are seeking a Data Analyst to join our growing Fraud Analytics team.

We operate in a data-rich, fast-paced environment, processing billions of data points annually, and play a critical role in safeguarding large enterprises from fraud. In this role, you will work at the intersection of data analysis, fraud strategy, and automation, collaborating closely with engineering, data science, and commercial teams to develop scalable fraud detection solutions.

This is a high-impact role with significant ownership and cross-functional collaboration in a team with tremendous room for growth. If you are highly motivated, data-driven, and thrive in a fast-moving environment - you belong with us.

Key Responsibilities

Develop and refine fraud detection strategies by analyzing complex datasets and identifying fraud patterns.

Partner with cross-functional teams, including software engineers, data scientists, and commercial stakeholders, to develop scalable fraud solutions.

Conduct deep-dive risk analyses, leveraging multiple data sources to assess fraud threats and define innovative solutions.

Monitor and automate fraud detection processes to enhance efficiency and effectiveness.

As a Fraud Data Scientist, you will be at the front lines of protecting our ecosystem from sophisticated financial fraud and abuse. You will join a high-impact team operating in a data-rich, high-frequency environment where seconds matter.

In this role, you will take ownership of the end-to-end machine learning lifecycle-from uncovering complex fraud patterns to deploying highly scalable, real-time models into production. You will collaborate closely with Engineering, Product, and Risk Operations to build robust defenses that balance strict security with a seamless user experience.

What You Will Be Doing
Model Development & Deployment: Design, train, and deploy advanced machine learning models (e.g., gradient boosting, anomaly detection, graph networks) to detect and mitigate fraud in real-time.

Production Ownership: Take full ownership of putting models into production systems, ensuring low-latency execution and high reliability.

Agentic Workflows: Research, build, and implement Agentic flows and LLM-driven orchestration to automate multi-step fraud decisioning, logic routing, and investigation paths.

Adversarial Analysis: Conduct deep-dive exploratory analysis on massive datasets to identify emerging fraud vectors, loops, and coordinated attacks.

Feature Engineering: Build and optimize real-time streaming and batch features to improve model signal and precision.

Experimentation & Monitoring: Design rigorous shadow-testing and A/B testing frameworks for new models. Set up continuous monitoring pipelines to catch data drift and performance degradation early.

As we scale and evolve our fully automated fraud prevention strategies, we are seeking a Senior Data Analyst to join our growing Fraud Analytics team.

We operate in a data-rich, fast-paced environment, processing billions of data points annually, and play a critical role in safeguarding large enterprises from fraud. In this role, you will work at the intersection of data analysis, fraud strategy, and automation, collaborating closely with engineering, data science, and commercial teams to develop scalable fraud detection solutions.

This is a high-impact role with significant ownership and cross-functional collaboration in a team with tremendous room for growth. If you are highly motivated, data-driven, and thrive in a fast-moving environment - you belong with us.


Key Responsibilities

Develop and refine fraud detection strategies by analyzing complex datasets and identifying fraud patterns.

Partner with cross-functional teams, including software engineers, data scientists, and commercial stakeholders, to develop scalable fraud solutions.

Conduct deep-dive risk analyses, leveraging multiple data sources to assess fraud threats and define innovative solutions.

Monitor and automate fraud detection processes to enhance efficiency and effectiveness.