Campus AI Research Engineer
You apply advanced techniques to challenging domains, collaborate with researchers and quants on reusable financial AI and machine learning frameworks, optimize high-performance computing training pipelines, integrate low-latency models into production systems, and build observable, performant large-scale systems using C, C++, Python, CUDA, and related languages.
Responsibilities
- Apply advanced techniques to complex domains
- Collaborate with researchers and quants to build reusable financial AI and machine learning frameworks
- Optimize training pipelines for high-performance computing resources
- Integrate AI and machine learning models into latency-sensitive production systems
- Develop large-scale AI and machine learning systems
- Reduce research iteration cycle time
Requirements
- Proficiency in Python and/or C++
- Proficiency in PyTorch, JAX, TensorFlow, or similar frameworks
- GPU or accelerator programming experience with CUDA, Triton, SYCL, ROCm, or equivalent
- Experience building AI and machine learning systems at scale
- Experience with large-scale training data and low-latency or high-throughput inference
- Strong written and verbal communication skills in English
- Reliable and predictable availability