A proprietary trading firm specializing in quantitative and algorithmic trading is seeking a Software Engineer to enhance their trading systems and develop state-of-the-art AI-driven models.
Software Engineer - AI & Machine Learning (Trading Firm)
Location: Chicago
Employment Type: Full-time
About Us:
A leading proprietary trading firm specializing in quantitative and algorithmic trading across global financial markets is seeking a Software Engineer - AI & Machine Learning to enhance their trading systems and develop state-of-the-art AI-driven models.
Role Overview:
As an AI-focused Software Engineer, you will design, implement, and optimize machine learning models to enhance our trading strategies and market predictions. You will work closely with quantitative researchers, traders, and software engineers to integrate AI solutions into our high-frequency and low-latency trading systems.
Key Responsibilities:
• Develop and implement AI/ML models for market prediction, trade execution, and portfolio optimization.
• Design and optimize deep learning and reinforcement learning algorithms for trading applications.
• Build and maintain scalable AI-driven software pipelines to support real-time decision-making.
• Collaborate with quant researchers and traders to refine trading strategies using AI insights.
• Optimize algorithms for performance, latency, and computational efficiency in a high-frequency trading environment.
• Leverage big data technologies and cloud computing to enhance model training and backtesting.
• Monitor and improve AI models through continuous learning, retraining, and feature engineering.
Requirements:
• Education: Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, Mathematics, or a related field.
• Programming Skills: Proficiency in Python, C++, or Java. Strong experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Machine Learning Expertise: Hands-on experience in deep learning, reinforcement learning, time-series forecasting, and NLP.
• Trading Knowledge: Understanding of financial markets, order execution, and quantitative strategies is a plus.
• Big Data & Infrastructure: Experience with distributed computing (Spark, Ray), cloud platforms (AWS, GCP), and database management (SQL, NoSQL).
• Optimization & Performance: Knowledge of high-performance computing and low-latency systems.
• Problem-Solving: Strong analytical skills and ability to work in a fast-paced, results-driven environment.
Preferred Qualifications:
• Experience in high-frequency trading (HFT) or systematic trading strategies.
• Familiarity with trading APIs, FIX protocol, and algorithmic order execution.
• Background in signal processing, Bayesian methods, or statistical arbitrage.
• Contributions to AI research or open-source ML projects.
