Description
:
Summer 2026 Internship - Machine Learning Engineer Intern
Application Deadline: February 27, 2026
We encourage you to submit your application as early as possible, as internship applications are reviewed on a rolling basis.
Internship Dates: June 8, 2026 – August 14, 2026
(You must be available to work during this period.)
The internship is finalized through a tripartite agreement between the selected student, their university and Dow Jones. We recommend that you check with your university that you are eligible to complete this internship as a part of your degree/program before application.
About Us:
Dow Jones is a global provider of news and business information, delivering content to consumers and organizations around the world across multiple formats, including print, digital, mobile and live events. Dow Jones has produced unrivaled quality content for more than 130 years and today has one of the world’s largest news-gathering operations globally. It is home to leading publications and products including the flagship Wall Street Journal, America’s largest newspaper by paid circulation; Barron’s, MarketWatch, Mansion Global, Financial News, Investor’s Business Daily, Factiva, Dow Jones Risk & Compliance, Dow Jones Newswires, OPIS and Chemical Market Analytics. Dow Jones is a division of News Corp (Nasdaq: NWS, NWSA; ASX: NWS, NWSLV).
About the Role:
We are looking for a detail oriented and motivated person to join our team as a Machine learning engineer Intern. As a member of the Dow Jones AI Engineering team, you’ll have the opportunity to gain hands-on experience with our teams by designing, constructing, and maintaining machine learning pipelines tailored for various Artificial Intelligence (AI) applications, particularly focusing on Natural Language Processing (NLP). You will leverage your expertise in statistical analysis and machine learning (ML) techniques to derive insights from data, address the organization's needs, and deliver tangible value through actionable outcomes. Throughout the experience, you'll collaborate with and learn from highly skilled machine learning engineers, while also sharing your knowledge, as we continuously improve products loved by their users. Be part of a culture that fosters collaboration and allows unique perspectives to thrive.
You Will:
Collaborate within the AI Engineering Team to maintain robust data pipelines supporting various ML models, focusing on information retrieval applications.
Analyze and clean large datasets to optimize reusable ML models.
Partner with stakeholders across the company to translate business requirements into technical solutions.
Utilize analytical skills for NLP modeling, algorithm selection, and POC development.
Test alternative solutions to power and enhance AI applications.
Design and build intelligent AI systems, such as bots and summarization tools, that help customers work smarter and more efficiently with information.
Assist in evaluating machine systems and enhancing their performance.
You Have:
Currently pursuing or recently completed a STEM degree
Coding experience (python preferred, etc.)
Familiarity with Machine Learning (NLP preferred)
Attention to detail and eagerness to explore topics in depth
Proactive attitude and willingness to take on new challenges
Ability to quickly learn and adapt to new technologies and tools
Familiarity with open source tools and models
Reasonable accommodation: Dow Jones, Making Careers Newsworthy - We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law. EEO/Disabled/Vets. We strongly encourage applications from all qualified individuals, including women, people with disabilities, and those from underrepresented groups. Dow Jones is committed to providing reasonable accommodation for qualified individuals with disabilities, in our job application and/or interview process.