Machine learning internship 2025 in distinguished financial technology companies such as Jane Street provides an ideal opportunity to enhance practical experience in the fields of machine learning and artificial intelligence. This program provides participants with an invaluable opportunity to apply their academic knowledge in a real and dynamic financial environment. This program also allows participants to work with elite experts in the field, and apply modern computing techniques in an innovative financial environment.
Overview
Jane Street was founded by a group of financial technology experts in New York. Today it is a leading global company with more than 2,600 employees in five offices around the world. The company focuses on using modern technologies, such as machine learning, to analyze trading data and make informed investment decisions. The company specializes in trading various financial assets in more than 200 locations in 45 countries, creating a data-rich environment that relies on machine learning strategies.
Program details
Location: Jane Street offices around the world.
Duration of training: From June to September 2025.
Fields: The program includes diverse fields such as machine learning, computing, artificial intelligence, financial technology, and software.
Required language: Proficiency in English.
Tasks and responsibilities
- Trainees are paired with professional mentors to collaborate on real-world projects related to the development and analysis of linear and complex models.
- Build and apply machine learning models to analyze financial data and predict market movements.
- Analyze huge amounts of trading data using advanced Jane Street computing resources.
- Attend educational workshops, group discussions, and practical challenges to develop academic and professional skills.
- Trainees participate in social events and meetings with guest speakers to learn about industry best practices.
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Benefits of this Machine learning internship 2025
- The program provides an opportunity to work within a specialized team and benefit from academic and professional mentoring support.
- Access to a GPU network containing thousands of A/H100s units for big data analysis.
- Collaborate with elite financial technology professionals from various professional backgrounds.
- Explore career opportunities at Jane Street after the program, and continue learning through interactive activities and comprehensive educational materials.
- This training allows participants to work on real-world projects and apply their skills in a real-world work environment.
Requirements
- The candidate must be an undergraduate student, doctoral researcher, or postdoctoral researcher with practical experience in solving machine learning problems.
- Proficiency in the Python programming language, and the ability to apply logical and mathematical thinking to problems.
- The desire to ask questions, admit mistakes, and learn continuously.
- The ability to interact with colleagues from diverse professional backgrounds.
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How to apply for Machine learning internship 2025
You can apply by clicking on Apply Now to be directed to the official announcement of the opportunity or visit the company’s website janestreet.com. Applications are evaluated based on suitability and passion for learning.
FAQs
Is machine learning a good career in 2025?
Machine learning is considered one of the promising fields in the future, especially in 2025 in light of the technological development that the world has witnessed recently. Therefore, jobs in this field are considered among the highest paying jobs due to the small number of specialists in this field and the constant demand for them all over the world.
Where can I find a machine learning internship?
Our site is distinguished by the fact that it offers a large number of machine learning internships all over the world. All you have to do is follow the site daily to get the appropriate opportunity for training that qualifies you for the labor market directly so that you can easily find the appropriate opportunity to work in this field, which is characterized by competitive salaries.
