Campus ML Research Engineer

You will collaborate with researchers, quants, and engineers to build machine learning systems for quantitative finance. You will optimize training pipelines on high-performance computing resources, integrate low-latency inference systems into production, develop large-scale ML systems, and work with C, C++, Python, CUDA, and other GPU languages.

Responsibilities

• Apply state-of-the-art techniques to complex domains
• Build flexible and reusable frameworks for financial ML
• Optimize training pipelines for high-performance computing resources
• Integrate ML models into production systems
• Develop large-scale ML systems
• Improve research productivity by reducing iteration cycle time

Requirements

• Proficiency in Python and/or C++
• Proficiency in PyTorch, JAX, TensorFlow, or another deep learning library
• Expertise in GPU or accelerator programming, such as CUDA, Triton, SYCL, or ROCm
• Experience building large-scale ML systems
• Excellent written and verbal communication skills in English
• Reliable and predictable availability