Campus AI Research Engineer - Deep Learning (Intern)
Core
Research engineer applying state-of-the-art deep learning and AI techniques to build flexible, reusable frameworks for financial ML and integrate models into low-latency production systems.
Role type
Campus AI Research Engineer (Deep Learning) - Intern
Builds
Large-scale, observable, and performant ML systems for quantitative trading
Domain
Quantitative finance / Financial markets
Deliverable
production ML models
Required skills
Modern deep learning techniques, language modeling architectures (transformers, SSMs), Python, C++, PyTorch, JAX, TensorFlow, HPC training, GPU performance optimization (CUDA/ROCm)
Preferred skills
End-to-end model development, strong opinions on ML research tooling and infrastructure
Responsibilities
Apply state-of-the-art techniques to complex domains, build flexible and reusable frameworks for financial ML, optimize training pipelines to utilize HPC resources, integrate ML models into production systems where latency matters, build large-scale ML systems that are observable and performant
Seniority
Intern