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About the Role

G-Research is seeking an exceptional NLP Performance Engineer to join their NLP Engineering team, focusing on large-scale LLM inference performance. This role involves designing and implementing techniques to improve the performance, cost-efficiency, and capabilities of inference workloads on cutting-edge compute infrastructure, enabling researchers and engineers to maximize the use of current and future systems.

Responsibilities

Profiling, benchmarking and optimising large-scale LLM inference workloads across our compute infrastructure
Ensuring efficient deployment of the latest models across a range of GPU architectures, adapting the inference stack as hardware evolves
Designing and implementing inference optimisations while maintaining output quality
Developing reference implementations, libraries and tooling to improve the efficiency and reliability of NLP workloads
Collaborating with researchers, senior stakeholders and engineers to design optimised solutions
Working with systems, architecture and platform teams to evolve the compute stack and influence long-term platform decisions

Requirements

Proven experience profiling, benchmarking and optimising large-scale LLM 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, KV-cache behaviour, attention variants and performance bottlenecks
Hands-on experience with LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM or TGI, and the PyTorch ecosystem
Experience with inference optimisation techniques, including quantisation, speculative decoding and model parallelism across modern GPU 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

Skills

LLM inference
Natural Language Programming (NLP)
Performance optimisation
Transformer inference
LLM serving frameworks (vLLM, SGLang, TensorRT-LLM, TGI)
PyTorch ecosystem
Quantisation
Speculative decoding
Model parallelism
Python
CUDA
Building reliable systems for machine learning workloads
Communication

Location

London

Work Type

Full-time

Experience Level

Quantitative Developer

Education Level

Bachelor’s, Master’s or PhD in computer science, or equivalent experience

Salary/Compensations

Highly competitive compensation plus annual discretionary bonus

Benefits

Lunch provided (via Just Eat for Business)
Dedicated barista bar
35 days’ annual leave
9% company pension contributions
Informal dress code
Excellent work/life balance
Comprehensive healthcare
Life assurance
Cycle-to-work scheme
Monthly company events

About the Company

G-Research tackles complex problems in quantitative finance by bringing scientific clarity to financial complexity.
They unite world-class researchers and engineers in an environment that values deep exploration and methodical execution.
They are building a world-class platform to amplify their teams' most powerful ideas.

Equal Opportunity

G-Research is committed to cultivating and preserving an inclusive work environment.
We are an ideas-driven business and we place great value on diversity of experience and opinions.
We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section