Software Engineer Intern – Low-Latency Trading Systems

Job Description

Quantitative Developer Intern – Summer 2027 | Tower Research Capital

The Tone:
This is a temporary internship at Tower Research Capital, located in New York, NY and Chicago, IL. Tower Research Capital is a leading quantitative trading firm, founded in 1998, with a 25+ year track record of innovation. The firm builds its business on a high-performance platform and empowers independent trading teams to discover unique market opportunities. This role is essential for developing and optimizing the world-class electronic trading infrastructure that supports Tower’s global operations, enabling trading and research teams to perform at their best.

The TL;DR
• Role: Internship
• Type: Temporary
• Location: In-person, New York, NY and Chicago, IL
• Pay: $3500–$5700 weekly
• Team: Works with trading and research teams
• Mission: To design, optimize, and operate high-performance trading and training systems, utilizing data analysis and market observations.
• Tech Stack: C++, Python, Linux/Unix

What You’ll Actually Do
• System Architecture: Architect and optimize performant low-latency trading and high-throughput training systems.
• Collaboration: Work extensively with traders and researchers to understand and implement system requirements.
• Data Analysis Tools: Create tools to analyze data for patterns, supporting trading strategy development.
• Market Analysis: Make market observations and conduct post-trade analysis to refine strategies.
• Simulator Development: Develop, augment, and calibrate exchange simulators for testing and validation.

The Must-Haves
• Background: Currently pursuing a Bachelor’s, Master’s, or PhD degree in computer science, mathematics, physics, electrical engineering, or related fields.
• Experience: No specific prior professional experience is required for this internship, but strong problem-solving abilities are essential.
• Skills: Proficient in an object-oriented programming language (C++ and Python preferred), possess a working knowledge of Linux/Unix, demonstrate strong communication skills, and hold an interest in financial markets.
• Bonus: Past industry experience, experience as a Teaching Assistant and/or participation in relevant Olympiads, and familiarity with machine learning, data analysis, market research, and data modeling.