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G-Research

Quantitative finance research applying rigorous methods

NLP Performance Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeLondon, UKIn-person

About the Job

Requirements

  • A Bachelor's, Master's or PhD in computer science, or equivalent experience.
  • Proven experience profiling, benchmarking and optimising large-scale large language model inference workloads.
  • A scientific, evidence-led approach to performance optimisation, using rigorous benchmarking and reproducible measurement.
  • Deep understanding of transformer inference, including prefill versus decode, key-value cache behaviour, attention variants and performance bottlenecks.
  • Hands-on experience with large language model serving frameworks such as vLLM, SGLang, TensorRT-LLM or Text Generation Inference, and the PyTorch ecosystem.
  • Experience with inference optimisation techniques, including quantisation, speculative decoding and model parallelism across modern graphics processing unit architectures.
  • Strong software engineering skills, including Python, CUDA and building reliable systems for machine learning workloads.
  • Strong communication skills, with the ability to collaborate across research, infrastructure and engineering teams.

Responsibilities

  • Profile, benchmark and optimise large-scale large language model inference workloads across the compute infrastructure.
  • Ensure efficient deployment of the latest models across a range of graphics processing unit architectures, adapting the inference stack as hardware evolves.
  • Design and implement inference optimisations while maintaining output quality.
  • Develop reference implementations, libraries and tooling to improve the efficiency and reliability of Natural Language Processing workloads.
  • Collaborate with researchers, senior stakeholders and engineers to design optimised solutions.
  • Work with systems, architecture and platform teams to evolve the compute stack and influence long-term platform decisions.

About the Company

G-Research

Quantitative finance research applying rigorous methods

G-Research applies scientific rigour to solve complex challenges in financial markets. It brings together world-class researchers and engineers to develop data-driven models and trading ideas, testing them through rigorous experimentation and robust infrastructure. Unlike many traditional asset managers, its culture emphasizes deep exploration, reproducibility, methodical execution, and long-term thinking. The goal is to generate alpha through disciplined, evidence-based research that informs investment decisions and advances understanding of financial markets.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2001

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