Machine Learning Engineer
About The Role
We are partnered with a growing quantitative hedge fund leveraging cutting-edge technology and data science to drive investment strategies. The team is composed of world-class researchers, engineers, and financial professionals dedicated to innovation and performance.
Role Overview
They are seeking a highly skilled Machine Learning Engineer to join our research and engineering team. You will work on developing and deploying advanced ML models to uncover patterns in financial data, optimize trading strategies, and enhance decision-making processes.
Key Responsibilities
- Design, implement, and maintain scalable machine learning systems for financial prediction and modeling.
- Collaborate with quantitative researchers and data scientists to translate research ideas into production-grade models.
- Conduct rigorous backtesting and performance evaluation of ML-driven strategies.
- Optimize model performance and latency for real-time trading environments.
- Stay current with the latest ML research and apply relevant advancements to our workflows.
Qualifications
- Advanced degree (MS/PhD) in Computer Science, Machine Learning, Statistics, or a related field.
- Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Solid understanding of machine learning algorithms, statistical modeling, and data preprocessing.
- Experience working with large-scale time-series data, preferably in a financial context.
- Familiarity with cloud computing, distributed systems, and model deployment pipelines.
- Excellent problem-solving skills and attention to detail.
Preferred Experience
- Prior experience in quantitative finance or algorithmic trading.
- Knowledge of financial markets, instruments, and trading strategies.
- Experience with feature engineering and signal generation from noisy datasets.
What They Offer
- Competitive compensation and performance-based bonuses.
- Access to vast datasets and high-performance computing resources.
- Collaborative and intellectually stimulating work environment.
- Opportunities for professional growth and research publication.
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