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Tower Research Capital

Software Engineer Intern (Summer 2027)

New York$182k–$218.4kinternshipinternAdded today

About this role

Tower Research Capital seeks a Software Engineer Intern for Summer 2027 to contribute to their quantitative trading platform. You'll work on low-latency systems, data pipelines, and trading infrastructure while gaining exposure to world-class engineering talent in a collaborative NYC environment.

What you'll do

  • Optimize trading systems using network and systems programming to minimize latency
  • Design and build systems for collecting, analyzing, and visualizing large-scale market data
  • Develop data pipelines to capture and provide fast access to market and reference data
  • Build or enhance algorithmic trading systems
  • Create automation solutions and products to improve trading operations efficiency

What they're looking for

  • C++, Golang, Java, JavaScript, Python, or Rust
  • Low-latency systems programming
  • SQL and relational database design
  • Object-oriented programming and design patterns
  • Linux system administration and command line
  • Data pipeline and ETL development
  • Problem-solving and debugging
  • Communication and collaboration

Benefits

  • Housing accommodation provided
  • Competitive compensation ($3,500–$4,200 weekly base)
  • Free daily breakfast, lunch, and snacks
  • Mentorship from senior staff and alumni network
  • Social events and networking opportunities (Broadway, escape rooms, cooking classes)
  • Collaborative, ego-free workplace culture
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Tower Research Capital

Tower Research Capital builds high-performance quantitative trading systems and infrastructure, serving traders and researchers with low-latency platforms for market data, strategy execution, and order management. The company is hiring software engineers, quantitative developers, and infrastructure specialists to design scalable systems, optimize trading platforms, and enhance development tooling.

View all jobs at Tower Research Capital

Likely interview questions

  • Walk us through a low-latency optimization problem you've solved; what techniques did you use?
  • Describe your experience building or optimizing data pipelines—what was your bottleneck and how did you address it?
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