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Thurn Partners · Miami
A top-tier global trading firm is building out its post-training research. The mandate is to take large pretrained models and adapt them to financial markets. Those models have to deal with noisy data, distributions that shift daily, and competitors who adapt to any edge. They also have to run within tight latency budgets. Performance is measured against real market outcomes rather than benchmarks or human raters. The firm trades at a scale few can match, so small model improvements have a measurable effect within days. You will join a small group of researchers whose work goes straight into production.
THE
Fine-tune, distil and align large models for domain-specific tasks
Build evaluation that measures what matters, not what is easy to measure
Quantize, prune and optimize inference where latency carries a direct cost
Write and profile custom GPU kernels when standard ops become the bottleneck
Python: PyTorch, JAX, NumPy, Polars
GPU: CUDA, Triton, Nsight, NCCL
C++17/20, pybind11
A degree in a quantitative field from a leading university, with a minimum GPA of 3.5/4.0
Production-quality Python and C++
GPU knowledge below the API: memory hierarchy, occupancy, and how to diagnose a slow kernel
A PhD or Master's in machine learning, computer science, mathematics, statistics or physics
Leadership experience within ML roles, such as technical lead, mentoring or owning a workstream
HOW
You start on problems without waiting to be asked, and you know when to bring in your lead
You treat feedback as data and change course when it is right
You want to be the least experienced person in the room some days, because that is where the learning is
PRE
Please do not apply if you're looking for a contract or remote work.
You must be eligible to live and work in the US, without requiring sponsorship.
Allow 1-5 working days for a response to any job enquiry.
Your application is subject to our privacy policy (thurnpartners.com/privacy-policy).
Details
| Company | Thurn Partners |
| Location | Miami |
| Type | FULL TIME |
| Niche | Full-time |