Senior Machine Learning Researcher, Post-Training & Inference Optimization

Thurn Partners Ltd; New York (NY); Sur place; USD 180 000 - 240 000; Plein temps

Résumé du poste

Thurn Partners Ltd in New York (US) seeks a senior ML researcher to join its post-training research team. You will fine-tune large models for financial markets, align them for domain tasks, and push results to production with engineering and trading teams.

Applicants should have production-quality Python and C++, GPU proficiency, and hands-on post-training ML experience, with US work eligibility.

Qualifications

• Industry experience in ML roles with hands-on post-training work.
• Production-quality Python and C++.
• GPU knowledge beyond the API: memory hierarchy and occupancy.
• Eligibility to work in the US.

Responsabilités

• 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.
• Take research into production with engineering and trading teams.

Connaissances

Python

C++

GPU programming

Post-training ML

Latency optimization

Formation

Bachelor's degree in a quantitative field

PhD or Master's in ML/CS/Math/Statistics/Physics

Outils

CUDA

Triton

Nsight

NCCL

pybind11

DeepSpeed

Megatron

FSDP

Description du poste

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 ROLE:

• 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
• Take research into production with engineering and trading teams

STACK:

• GPU: CUDA, Triton, Nsight, NCCL
• C++17/20, pybind11
• FSDP, DeepSpeed or Megatron-style parallelism

REQUIRED:

• A degree in a quantitative field from a leading university, with a minimum GPA of 3.5/4.0
• Industry experience in ML roles, with hands-on post-training work
• Production-quality Python and C++
• GPU knowledge below the API: memory hierarchy, occupancy, and how to diagnose a slow kernel
• Eligibility to work in the US

PREFERRED:

• 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 WORK:

• 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 APPLICATION:

• 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.
• Please ensure you meet the required experience section prior to applying.
• Allow 1-5 working days for a response to any job enquiry.
• Your application is subject to our privacy policy (thurnpartners.com/privacy-policy).