Position Description

As a MLE-Systematic Trading (Trading & Financial Systems), you will build and optimize high-performance trading systems and quantitative infrastructure that power our brokerage operations. Working alongside experienced quants and treasury, you will develop production-grade systems for algorithmic trading, risk management, and market analysis using both classical quantitative methods and modern machine learning techniques. This role offers an excellent opportunity to apply strong technical skills to real trading challenges while deepening your expertise in quantitative finance, system design, and financial engineering.

What You Will Be Doing:

• Design and implement trading systems including flow analysis, hedging algorithms, position management, and risk controls for live market operations

• Build and maintain quantitative infrastructure for backtesting, strategy simulation, and performance analysis with robust data pipelines

• Develop pricing models, hedging systems, and portfolio optimization algorithms using mathematical finance and quantitative methods

• Implement real-time market data processing systems and trading APIs for exchanges, brokers, and liquidity providers

• Create monitoring and analytics tools to track trading performance, market conditions, and system health in production environments

• Apply machine learning techniques to enhance trading signals, pattern recognition, and anomaly detection where appropriate

• Maintain and improve existing trading infrastructure with focus on reliability, scalability, and operational excellence

What You Need to Be Successful in This Role:

• Bachelor's or Master's degree in Computer Science, Financial Engineering, Mathematics, Physics, Statistics, or related quantitative field

• 2+ years of professional experience in quantitative development, algorithmic trading, or financial systems engineering

• Strong programming skills in Python with deep knowledge of numerical computing libraries (numpy, pandas, scipy) and experience with performance optimization

• Solid understanding of financial markets including trading mechanics, order types, market microstructure, and derivatives (futures, options)

• Hands-on experience building trading systems or financial applications - including backtesting frameworks, execution algorithms, or risk management systems

• Knowledge of quantitative finance concepts including P&L calculation, position sizing, portfolio risk metrics, and basic derivatives pricing

• Strong mathematical foundation with ability to implement quantitative models and statistical methods from research papers

• Experience with APIs for financial data providers and trading platforms (exchange APIs, market data feeds, execution venues)

• Self-motivated with ability to work independently and take ownership of projects from design through production deployment

What Makes You Stand Out:

• Direct experience with brokerage operations, cryptocurrency trading systems, arbitrage strategies, or cross-exchange operations

• Knowledge of market-making, and systematic trading strategies

• Experience with real-time data streaming (WebSocket, message queues) and low-latency system design

• Familiarity with modern ML frameworks (PyTorch, scikit-learn) and their application to financial prediction problems

• Track record of deployed trading systems or quantitative strategies in live markets

• Understanding of regulatory and compliance considerations in trading operations

• Contributions to quantitative finance open-source projects or published research