Campus AI Researcher - ML for Quant Trading

Tradermath

Greater London

Hybrid

GBP 90,000 - 130,000

Full time

14 days+
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Job summary

Jump Trading Group is seeking research scientists with a demonstrated ability to apply machine learning to state-of-the-art capabilities in complex domains. The ideal candidate will implement an open-ended research project from concept to production and continuously improve model design, tools, and infrastructure.

Projects may target any area of the quantitative research and monetisation process. We expect a strong publication record, deep learning experience with transformers or language

Qualifications

  • Strong publication record at major ML conferences.
  • Deep learning background with language modeling exposure.
  • Proficient in Python and C++ development.
  • Experience with PyTorch, TensorFlow or JAX.
  • Curiosity, versatility and pragmatism in research.
  • Ability to work collaboratively with researchers.
  • Ability to reason quantitatively and communicate clearly.
  • Reliable and predictable availability for projects.

Responsibilities

  • Apply machine learning to achieve state-of-the-art capabilities.
  • Lead an open-ended research project from concept to production.
  • Continuously improve model design, tools and infrastructure.
  • Explore areas across the quantitative research and monetisation process.
  • Perform other duties as assigned.

Skills

Publication record
ML & DL modeling
Python & C++
Transformers / language models
Collaboration & teamwork
Quantitative problem solving
Availability & reliability

Tools

PyTorch
TensorFlow
JAX
CUDA

Job description

Jump Trading Group is seeking research scientists with a demonstrated ability to apply machine learning to state-of-the-art capabilities in complex domains. The ideal candidate will implement an open-ended research project from concept to production and continuously improve model design, tools, and infrastructure.

Projects may target any area of the quantitative research and monetisation process. We expect a strong publication record, deep learning experience with transformers or language

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