About Hellyeah AI

Hellyeah AI is building AI-powered solutions to help businesses make better decisions through advanced automation, data intelligence, and algorithmic systems.

We are looking for a Senior Quantitative Engineer / Algo Engineer to join our engineering team and build the next generation of quantitative strategy infrastructure. The ideal candidate has experience from top quantitative trading firms, hedge funds, or financial technology companies, with strong expertise in algorithm development, quantitative research infrastructure, and large-scale backtesting systems.

Responsibilities

Design, develop, and optimize quantitative trading strategies and algorithmic models

Build and maintain high-performance backtesting and simulation frameworks

Develop research infrastructure that enables rapid strategy iteration and validation

Collaborate with quantitative researchers to translate trading ideas into production-ready systems

Implement data pipelines, signal generation frameworks, and strategy evaluation tools

Improve the accuracy, scalability, and performance of simulation environments

Conduct strategy analysis, performance attribution, and model optimization

Ensure research results can be reliably transitioned into production systems

Requirements

5+ years of experience in quantitative development, algorithm engineering, or related fields

Experience working at leading quantitative trading firms, hedge funds, proprietary trading firms, or financial technology companies preferred

Strong experience building quantitative research platforms, backtesting engines, or trading infrastructure

Strong programming skills in Python and/or C++

Solid understanding of algorithmic trading, quantitative strategies, and financial data systems

Experience with large-scale time-series data processing and performance optimization

Strong problem-solving ability and engineering mindset

Preferred Qualifications

Experience with systematic trading strategies, factor models, or machine learning-based trading systems

Experience building low-latency or high-performance simulation systems

Background in mathematics, statistics, computer science, or related technical fields

Experience with market microstructure, execution models, or portfolio optimization