Software Engineer

Role Overview

Trexquant is seeking talented Infrastructure Engineers to join our high-performance engineering teams. During the application process, we assess core skills first and then match candidates to the team that best aligns with their strengths—whether in C++ Trading Systems, Simulation Engineering, or Data Infrastructure.

Key Responsibilities

• Full lifecycle development of low-latency/high-throughput research and trading systems using C++ & Python.
• Build and optimize data processing pipelines to ensure reliable access to large, high-quality datasets for systematic strategies.
• Assist in developing tools for back testing, model training, and strategy evaluation.
• Collaborate with quantitative researchers and traders to deliver technical solutions that improve research productivity and trading performance.
• Maintain high-quality standards through active participation in code reviews, rigorous testing, and documentation.
• Stay abreast of emerging technologies and best practices to continuously innovate our systems.

Requirements

• Bachelor's, Master's, or PhD in Computer Science or a related STEM discipline.
• Minimum 2 years of experience in C++ software development within demanding, real-time environments (HFT).
• Strong expertise in modern C++ (C++17/20), including advanced features such as template metaprogramming.
• Demonstrated experience building high-throughput, low-latency systems.
• Deep understanding of Linux fundamentals and systems-level programming.
• Familiarity with distributed systems technologies like Kafka, Redis, or HTCondor is a plus.
• Working knowledge of Python and its numerical ecosystem (NumPy, SciPy).
• Strong analytical thinking and problem-solving skills to operate independently in fast-paced environments.

Good to Have

• Experience with matrix computation/optimization libraries (Blaze, OpenBLAS, LAPACK).
• Familiarity with live market data feeds and exchange connectivity.
• Skill in profiling and tuning production Linux systems for high throughput.
• Background in time-series processing or event-driven architectures.
• Experience bridging C++ and Python (pybind11, C API, hybrid pipelines).