Madison-Davis
Overview
A high-performing quantitative trading firm is growing its core technology group and looking for a hands-on C++ Engineer to help design and optimize the research and trading systems that drive its global strategies. This role sits at the intersection of software engineering and quantitative research, offering the chance to directly influence system performance, model scalability, and trading execution efficiency.
The ideal candidate will bring strong software engineering fundamentals and experience building or optimizing low-latency, high-throughput systems —preferably within data-intensive or trading environments.
Key Responsibilities
Design, build, and maintain core infrastructure supporting quantitative research, simulation, and live trading workflows
Develop and optimize C++ systems for performance, scalability, and reliability, with a focus on data processing, model computation, and integration
Implement and tune data pipelines and computation engines for fast, accurate access to large datasets
Automate and streamline research workflows for model training, evaluation, and deployment
Partner with quantitative researchers and traders to develop systems that enhance research productivity and execution performance
Produce clear technical documentation and provide ongoing support for internal users
Required Skills & Experience
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field
2+ years of experience writing production-grade C++ (C++17 / C++20), with deep understanding of algorithms, data structures, and concurrency
Proven experience building or optimizing low-latency, high-performance distributed systems
Familiarity with real-time data pipelines, research or simulation infrastructure, or large-scale computational systems
Python experience a strong plus, especially for automation or research tooling
Background in trading, financial systems, or other high-performance computing environments is beneficial but not required
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The ideal candidate will bring strong software engineering fundamentals and experience building or optimizing low-latency, high-throughput systems —preferably within data-intensive or trading environments.
Key Responsibilities
Design, build, and maintain core infrastructure supporting quantitative research, simulation, and live trading workflows
Develop and optimize C++ systems for performance, scalability, and reliability, with a focus on data processing, model computation, and integration
Implement and tune data pipelines and computation engines for fast, accurate access to large datasets
Automate and streamline research workflows for model training, evaluation, and deployment
Partner with quantitative researchers and traders to develop systems that enhance research productivity and execution performance
Produce clear technical documentation and provide ongoing support for internal users
Required Skills & Experience
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field
2+ years of experience writing production-grade C++ (C++17 / C++20), with deep understanding of algorithms, data structures, and concurrency
Proven experience building or optimizing low-latency, high-performance distributed systems
Familiarity with real-time data pipelines, research or simulation infrastructure, or large-scale computational systems
Python experience a strong plus, especially for automation or research tooling
Background in trading, financial systems, or other high-performance computing environments is beneficial but not required
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