ML Engineer

About Us

We are an elite, technology-driven hedge fund based in Boston, managing billions in assets across global markets. Our firm thrives on innovation, rigorous research, and cutting-edge technology. We foster a collaborative, intellectually curious environment where top talent builds proprietary systems and strategies to gain a competitive edge.

The Role

We're seeking a highly skilled Machine Learning Engineer to join our Quantitative Research & Technology team. You will play a pivotal role in developing and deploying advanced ML models that drive investment strategies, risk management, and decision-making across the firm. This is a high-impact role with direct exposure to portfolio managers, researchers, and technologists.

Responsibilities

• Design, implement, and deploy machine learning models to support quantitative research and trading.
• Collaborate with data scientists and quant researchers to identify opportunities for ML applications.
• Build robust pipelines for data ingestion, feature engineering, training, and real-time inference.
• Evaluate and optimize model performance in live trading environments.
• Maintain and enhance infrastructure for model versioning, monitoring, and deployment.
• Contribute to research on novel ML techniques applicable to finance.

Qualifications

• 3-6+ years of experience in machine learning engineering, preferably in a quantitative or financial setting.
• Strong programming skills in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Deep understanding of modern ML techniques, including supervised/unsupervised learning, deep learning, and time-series modeling.
• Experience deploying models in production, preferably in low-latency or high-throughput environments.
• Familiarity with financial markets, quantitative modeling, or trading systems is a strong plus.
• Bachelor's, Master's, or Ph.D. in Computer Science, Machine Learning, Applied Mathematics, or a related field.