Real-Time ML Engineer (Trading & GPU Platforms)

IMC; City Of London; On-site; GBP 90,000 - 150,000; Full time

Job summary

IMC, a leading research-driven trading firm, seeks an experienced Machine Learning Engineer to build and optimise systems for training and inference at scale across global operations. You will collaborate with quantitative researchers, hardware specialists and software engineers to accelerate experimentation, training speed and real-time deployments.

You will contribute to ML Research Engineering and ML Performance Engineering, leveraging GPU acceleration and low-level optimisations to push the

Qualifications

• 3+ years of experience in machine learning, focusing on training or inference systems.
• Production software engineering with ownership of deployed systems.
• Solid understanding of modern ML workloads and model behaviour.
• Systems mindset with emphasis on measurement for performance, scale or reliability.
• Strong collaboration and ability to justify technical decisions across teams.

Responsibilities

• Develop large-scale distributed training pipelines for complex datasets and models.
• Partner with quantitative researchers to automate ML experiments, hyperparameter tuning and retraining.
• Work with HPC specialists to optimise workflows, improve training speed and reduce compute cost.
• Build and optimise low-latency inference pipelines for real-time production use.
• Extend and improve ML frameworks and open-source tools for better performance.
• Design scalable model infrastructure for high-volume trading data and real-time predictions.
• Evaluate and adopt third-party tools to enhance model development and inference.

Skills

Python

Production software engineering

ML fundamentals

Systems mindset

Collaboration

Tools

PyTorch

TensorFlow

JAX

CUDA

Job description

IMC, a leading research-driven trading firm, seeks an experienced Machine Learning Engineer to build and optimise systems for training and inference at scale across global operations. You will collaborate with quantitative researchers, hardware specialists and software engineers to accelerate experimentation, training speed and real-time deployments.

You will contribute to ML Research Engineering and ML Performance Engineering, leveraging GPU acceleration and low-level optimisations to push the