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Strong brand and metro location increase competition, but niche low-latency C++ requirements limit applicant pool.
High because low-latency C++ systems and trading infrastructure skills are highly domain-specific and less transferable.
High due to explicit 2+ years C++ requirement, systems/kernel expertise, and performance engineering mandates.
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Own full lifecycle development of low-latency, high-throughput quantitative research and trading systems using modern C++ and Python.
Architect and optimize large-scale data pipelines for real-time financial data ingestion and processing.
Collaborate closely with quantitative researchers and traders to build tooling for model training, back-testing, and strategy evaluation.
Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, or a related STEM discipline.
Minimum 2 years professional experience with modern C++ (C++17/20) in demanding, real-time or low-latency environments.
Strong Linux systems knowledge including kernel tuning and systems-level programming.
Proficient in Python and its numerical computing libraries (NumPy, SciPy).
Experienced in building and optimizing ultra-low latency or high-throughput financial or similarly demanding infrastructure.
Comfortable operating in a high-stakes, fast-paced environment collaborating with quantitative researchers and traders.
Skilled in cross-language integration between C++ and Python and familiar with distributed system technologies is a strong plus.