AI & Emerging technologies

AI Research Engineer, Pre-Training

Hudson River Trading

London · Greater London · United Kingdom

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Overview

As an AI Research Engineer (Pre-training) on the HAIL team, you will advance large-scale model training for market-focused foundation models. You’ll collaborate with researchers to co-design, optimize training systems, and scale GPUs across busy clusters. This role blends deep engineering with research to push performance, fault tolerance, data pipelines, and parallelism in a demanding, finance-oriented environment. You’ll impact trading outcomes by improving the core infrastructure that drives state-of-the-art models.

Pay / Benefits
  • discretionary performance-based bonuses
  • competitive benefits package
  • salary range USD per year
  • global offices
  • equal opportunity employer
Responsibilities
  • Improve large-scale model training end-to-end (kernel development, data loading, parallelism, networking, fault-tolerance)
  • Collaborate with researchers to co-design and enhance models and research agenda
  • Manage and optimize GPU clusters for high-performance training
  • Advance systems capabilities across kernel, framework, and toolchains (CUDA, PyTorch/JAX/XLA, CUDA Graphs)
  • Develop and maintain scalable training pipelines and fault-tolerant workflows
  • Contribute to a culture of experimentation and rapid iteration to squeeze performance from systems
Key requirements
  • Strong engineering skills in CUDA/Triton/Pallas/CuTe DSL kernel development
  • Lower-level PyTorch/JAX/XLA development experience
  • CUDA Graphs or FPGA/ASIC experience
  • Two+ years building deep learning systems across domains
  • Experience translating methods between applications; LLM experience valued but not required
  • Finance experience not required
  • Collaborative mindset
  • Strong problem-solving and cross-disciplinary communication
  • Adaptability in a fast-growing environment
  • CUDA/Triton/Pallas/CuTe DSL kernel development
  • Lower-level PyTorch/JAX/XLA development
  • CUDA Graphs

Reference: WJ-747_31204531 · Posted 01 Nov 2026, 12:14 PM

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