Machine Learning Research Engineer – Global Trading Firm

Job Overview:

Our client, a global leader in quantitative trading, is seeking a Machine Learning Research Engineer to join their New York team. This is a unique opportunity to contribute to a high-impact AI initiative developing advanced ML infrastructure and deep learning models that enhance trading strategies and performance.

Key Responsibilities:

• Conduct innovative research on deep learning models for price forecasting and market prediction.
• Design and optimize large-scale training and inference pipelines for deep learning.
• Explore and extend open-source ML frameworks to improve their functionality and performance.
• Collaborate with quants, researchers, and engineers to deploy machine learning innovations into trading systems.

Qualifications:

• PhD or equivalent experience in machine learning, computer science, or a related field.
• Proven expertise in deep learning using PyTorch, TensorFlow, or JAX.
• Strong Python programming skills and experience working with large-scale datasets.
• Background in computationally intensive or performance-optimized ML research.

Preferred: Experience with GPUs or accelerators (CUDA, Triton, Pallas), JAX ecosystem (XLA, Flax), distributed training, C++ programming, or a strong publication record (e.g., NeurIPS, ICML).

Why Join:

Be part of a collaborative, world-class environment where cutting-edge research directly influences trading outcomes. You’ll work alongside top engineers and scientists from around the globe, driving innovation at the intersection of AI and high-performance finance.