Quantitative Systems Engineer – Low-Latency Trading & ML

AXQ Capital; New York (NY); On-site; Full time

Job summary

A leading investment management firm in New York is seeking a Quantitative Researcher to develop state-of-the-art systems for quantitative trading. The role involves collaborating on strategy research, building low-latency systems, and optimizing trading infrastructures. Candidates should have a bachelor’s degree in a relevant field, be proficient in Python, and have prior experience in quantitative investing. Join us to drive innovation in trading strategies.

Qualifications

• Bachelor’s degree or above from a top-tier university.
• Prior work or internship experience in quantitative investing.
• Awards in national or international Olympiads (Mathematics, Physics, Computer Science) are a plus.

Responsibilities

• Collaborate closely with teams for strategy research and risk management.
• Build low-latency systems to process data streams in real time.
• Research technology models to enhance machine-learning predictions.
• Optimize low-latency trading infrastructure and risk-control systems.
• Leverage cloud services for dynamic resource management.

Skills

Proficient in Python

Familiarity with Go or C++

Experienced with data-processing libraries such as NumPy and Pandas

Comfortable working in Linux

Strong understanding of computer networking

Excellent communication skills

Education

Bachelor’s degree in Computer Science, Natural Sciences, Engineering, or Financial Mathematics

Job description

A leading investment management firm in New York is seeking a Quantitative Researcher to develop state-of-the-art systems for quantitative trading. The role involves collaborating on strategy research, building low-latency systems, and optimizing trading infrastructures. Candidates should have a bachelor’s degree in a relevant field, be proficient in Python, and have prior experience in quantitative investing. Join us to drive innovation in trading strategies.