Campus ML Research Engineer (Intern)
- Apply state-of-the-art techniques to complex and challenging domains.
- Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
- Optimize training pipelines to make the best use of our HPC resources.
- Integrate ML models into production systems where latency matters.
- Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
- Build large scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle time on research.
- Other duties as assigned or needed.
- Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
- Proficiency in Python and/or C++
- Proficiency in Pytorch, JAX, Tensorflow or other DL library.
- Ability to thrive in a collaborative, team-oriented environment
- Expertise in GPU or Accelerator programming (CUDA, Triton, SYCL, ROCm or equivalent)
- Experience building ML systems at large scale (hundreds of TBs of training data, low latency or high throughput inference requirements)
- Excellent written and verbal communication skills in English
- Reliable and predictable availability required
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