Low Latency Engineer

AXQ Capital; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

AXQ Capital, a global quantitative investment firm, is seeking a low-latency engineer to join our high-frequency trading research and platform team in Singapore. You will contribute to data pipelines, time-series storage/retrieval, backtesting and research analytics in Python, and optimize strategy and execution logic in C++/Rust.

The role rewards fast learning, rigorous problem solving, and clear communication in a live trading environment, with a strong competitive programming background

Qualifications

• Bachelor's degree in CS, Math, Statistics, Physics, or related quantitative field.
• 0–3 years of professional experience.
• Competitive programming background (ICPC/IOI/NOI) weighted heavily.
• Strong in Python or C++/Rust; solid data structures and algorithms.
• Quick, proactive, and rigorous—learns fast and stays calm in live trading environments.

Responsibilities

• Research infrastructure building: data pipelines, time-series storage/retrieval, backtesting and simulation framework, research analytics and visualization tooling in Python.
• C++/Rust strategy optimization: implement, profile, and optimize strategy and execution logic; port validated Python research into production code.

Skills

Python

C++

Rust

Algorithms

Competitive programming

Education

Bachelor's degree in CS, Math, Statistics, Physics, or related quantitative field

Job description

AXQ Capital is a global quantitative investment firm with offices in New York, Beijing, Shanghai, and Hong Kong . We pursue consistent alpha through rigorous scientific research and sustained investment in technology and data infrastructure. Our strategies are deployed across global markets, spanning multiple geographies, asset classes, and trading horizons.

Role

As low-latency engineer, you will participate in the development of our high-frequency trading research and trading platform. Your responsibilities include:

• Research infrastructure building: data pipelines, time-series storage/retrieval, backtesting and simulation framework, research analytics and visualization tooling in Python.
• C++/Rust strategy optimization: implement, profile, and optimize strategy and execution logic; port validated Python research into production code.

Requirements

• Bachelor's degree in CS, Math, Statistics, Physics, or a related quantitative field, with 0-3 years of professional experience
• Exceptional problem-solving ability; competitive programming background (ICPC, IOI/NOI) weighted heavily
• Strong in Python or C++/Rust, eager to become strong in the other; solid fundamentals in data structures and algorithms
• Quick, proactive, and rigorous - learns fast, fixes what's broken unprompted, stays calm and detail-oriented in a live trading environment, and communicates clearly.