Campus ML Research Engineer (Intern)
Core
Build state-of-the-art ML systems for quantitative finance, optimizing training pipelines and integrating low-latency inference models.
Role type
Campus ML Research Engineer (Intern)
Builds
Production ML systems for financial markets
Domain
Quantitative finance / High-performance computing
Deliverable
production ML models
Required skills
Python, C++, PyTorch/JAX/TensorFlow, GPU/Accelerator programming (CUDA/Triton/SYCL/ROCm), large-scale ML system design, statistical analysis, data mining
Preferred skills
Experience with HPC clusters, low-latency inference optimization
Technologies
Python, C++, PyTorch, JAX, TensorFlow, CUDA, Triton, SYCL, ROCm
Responsibilities
Apply state-of-the-art techniques to complex domains; build flexible frameworks for financial ML; optimize training pipelines on HPC; integrate ML models into production systems; build large-scale observable and performant ML systems
Seniority
Intern