Quantitative Developer - AI/ML Buildout
About the Role
A leading high-frequency trading (HFT) firm is seeking a Quantitative Developer to join a new AI/ML-focused buildout within its systematic trading division. This team is at the forefront of integrating cutting-edge machine learning and deep learning techniques into high-performance trading strategies, leveraging vast datasets, low-latency infrastructure, and scalable computing.
This role is ideal for an exceptional engineer with strong ML knowledge and a passion for applying advanced computational techniques to financial markets. You will work closely with quant researchers, data scientists, and traders to develop robust, high-performance machine learning models that drive trading decisions.
Key Responsibilities
- Develop and optimize ML-driven trading models and strategies for high-frequency trading.
- Engineer scalable, high-performance infrastructure to support AI/ML research and live trading.
- Work with large-scale financial datasets, implementing data pipelines and feature engineering techniques.
- Optimize low-latency execution and inference of ML models in production environments.
- Collaborate with traders and quants to translate research into deployable trading algorithms.
- Ensure robustness, scalability, and performance of AI-driven trading systems.
Required Qualifications
- Strong programming skills in Python and/or C++ (low-latency systems experience preferred).
- Experience with machine learning frameworks (PyTorch, TensorFlow, JAX) and AI-driven model development.
- Familiarity with high-performance computing (HPC), distributed systems, or GPU acceleration (CUDA, Triton, Ray, etc.).
- Knowledge of quantitative finance, market microstructure, or statistical learning is a plus.
- Experience working in a low-latency or real-time computing environment is highly desirable.
- Bachelor's, Master's, or Ph.D. in Computer Science, Mathematics, Physics, or a related field.
Preferred Experience
- Prior work in HFT, proprietary trading, hedge funds, or systematic trading environments.
- Experience optimizing ML models for low-latency execution in production.
- Knowledge of reinforcement learning, Bayesian optimization, or time-series modeling in trading applications.
- Familiarity with cloud-based ML training and deployment (AWS/GCP/Azure).
Why Join?
- Opportunity to be part of a greenfield AI/ML initiative at a top-tier HFT firm.
- Work with world-class quants, engineers, and researchers solving cutting-edge problems.
- Competitive compensation with significant performance-based upside.
- Access to state-of-the-art compute resources and real-time market data.
If you're excited about pushing the boundaries of AI in high-speed trading, we'd love to hear from you. Apply now to be part of a pioneering team shaping the future of systematic trading.
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