Trexquant is a growing systematic fund at the forefront of quantitative finance, with a team of world-class researchers and engineers. As we continue to expand our trading operations, we are investing heavily in building the next generation of our quantitative research & trading platform.
Our Infrastructure Engineers are embedded within the following teams:
- C++ Trading Engineer
As a member of the Engineering team, you will focus on developing high-performance trading systems, designing and optimizing short-term trading signals in a high-frequency environment with strict latency and efficiency requirements. You will also support independent trading activities by building robust C++ systems, collaborating with researchers and technologists, and delivering solutions that have a direct and measurable impact on trading performance. - C++ Simulation Engineer
As a C++ Simulator Engineer, you will work closely with quantitative researchers and traders to design, develop, and optimize high-performance systems for algorithmic trading. Your responsibilities will include building and maintaining the core infrastructure for trading simulations. - Data Infrastructure Engineer
As a member of the Data team, you will focus on financial and market data development, building scalable, distributed pipelines for systematic web scraping and ingestion of diverse data sources, with strict latency and reliability requirements. You will also work on developing exchange connectivity solutions by creating high-performance C++ handlers to capture, process, and integrate real-time market data feeds.
When you apply for an Infrastructure role at Trexquant, we will first assess you on the core skills required for the Engineering team. During the interview process, we will be able to get to know you better, learn about your strengths and match you to the best team that closely aligns with your skills and preference.
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.
- Assist in developing tools for back testing, model training, and strategy evaluation.
- Collaborate with researchers and traders to deliver technical solutions that improve research productivity and trading performance.
- Participate in code reviews, testing, and documentation to maintain high-quality standards.
- Stay abreast of emerging technologies, tools, and best practices, bringing innovative ideas to continuously improve 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.
- Strong expertise in modern C++ (C++17/20), including advanced features such as template metaprogramming
- Demonstrated experience in building high-throughput, low-latency systems.
- Strong understanding of Linux fundamentals and systems-level programming.
- Familiarity with distributed systems and related technologies (e.g., Kafka, Redis, HTCondor) is a plus.
- Working knowledge of Python and its numerical ecosystem (NumPy, SciPy).
- Strong analytical thinking and problem-solving skills, with the ability to operate independently in a fast-paced environment.
- Experience working with matrix computation and optimization (Blaze, OpenBLAS, LAPACK)
- Experience working with live market data and exchange feeds.
- Experience profiling and tuning production Linux systems for high throughput.
- Experience working with time-series processing or event driven systems.
- Experience working across C++ and Python boundaries, such as with bindings (pybind11, C API), embedded Python, hybrid pipelines and orchestration.
- A background in finance is preferred but not required
Benefits
- Competitive salary plus bonus based on individual and company performance
- Work in a collaborative and friendly environment, participate in the decision-making process for research direction, and have the opportunity to lead on new ideas.
- Comprehensive benefits including healthcare and insurance.
What We Do
Being a quantitative finance firm that uses Machine Learning (ML) to create multi-asset portfolios and seek profit from the market, Trexquant has continuously improved its investment and research platform since starting operations, leveraging new and emerging technologies. Trexquant uses rigorous quantitative methods to create multi-asset portfolios in global markets. To do this, Trexquant develops trading signals using its vast and continuously growing collection of data variables used as inputs for more complex trading models called Strategies. The result is an ever-growing and adapting engine built from thousands of intricate models and tens of thousands of signals, tailor-made with the goal to outperform the market during any condition. Capital is managed across 5,500+ cash equity positions across the United States, Europe, Japan, Australia, and Canada.
