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Software Engineer, Data Scientist, AI Engineer (Applied​/Software)

Job in New York, New York County, New York, 10261, USA
Listing for: Thurn Partners
Full Time position
Listed on 2026-06-18
Job specializations:
  • Software Development
    Data Scientist, Software Engineer, AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below
Location: New York

Overview

Search Consultant | Introducing distinguished Technologists with Global Quant Trading firms

C++ Engineer - Low Level Trading Systems

Company Insight:

A leading global proprietary trading firm is looking for experienced Software Engineers to help shape the future of its growing US cash equities business. You'll work on high-impact projects at the intersection of software and finance, building cutting-edge systems that power some of the most advanced trading strategies in the industry.

This is an opportunity to contribute directly to the technical vision and execution of complex, ultra-low-latency trading infrastructure.

Responsibilities
  • Architect and implement high-performance infrastructure for low-latency equities trading
    , including OMS and EMS components.
  • Develop core systems that ingest and respond to market data from major US exchanges in microseconds or less.
  • Contribute to pricing models and research tools that support market-making and proprietary strategies in US single stocks and ETFs.
  • Optimize data pipelines and execution logic to improve trading speed and reduce latency across the stack.
  • Collaborate with FPGA engineers to integrate hardware acceleration into a modern software-driven architecture.
  • Work closely with traders, researchers, and fellow engineers to improve decision-making tools and execution models.
Qualifications
  • Proficiency in C++ or C; experience with additional object-oriented languages is a plus.
  • Proven experience building real-time, low-latency systems at scale.
  • Strong computer science fundamentals and an instinct for performance optimization.
  • A background working with FPGA-assisted systems is a strong plus.
  • Interest in high-performance systems and the ambition to push the limits of what's possible in electronic trading.
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