Machine Learning Engineer

IMC; City Of London; On-site; GBP 120,000 - 160,000; Full time

Job summary

IMC is a research-driven trading firm leveraging machine learning to advance its trading capabilities. We seek a Machine Learning Engineer to build large-scale training and real-time inference pipelines, collaborate with researchers and HPC specialists, and push the performance of GPU-accelerated systems.

You will work on distributed training, low-latency inference, and open-source ML tool integration to drive faster experimentation and real-time decision making in trading environments.

Qualifications

• 5+ years in ML with focus on training or inference systems.
• Real-time, low-latency ML pipelines in high-performance environments a strong plus.
• Proficiency in Python, CUDA, or C++.
• Knowledge of PyTorch, TensorFlow or JAX.
• GPU programming for training and inference acceleration (CuDNN, TensorRT).
• Experience with distributed training (Horovod, NCCL).
• Exposure to cloud platforms and orchestration tools.
• Open-source contributions in ML or distributed systems a plus.

Responsibilities

• Develop large-scale distributed training pipelines for datasets and models.
• Build and optimize low-latency inference pipelines for real-time predictions.
• Develop libraries to improve ML framework performance.
• Maximize training and inference performance using GPUs and acceleration libraries.
• Design scalable model frameworks for high-volume trading data and real-time predictions.
• Collaborate with researchers to automate ML experiments and model retraining.
• Partner with HPC specialists to optimize workflows and reduce costs.
• Evaluate and roll out third-party tools to enhance development and inference.
• Explore open-source ML tool internals to extend capabilities.

Skills

Python

CUDA

C++

PyTorch

TensorFlow

JAX

Horovod

NCCL

GPU acceleration

Distributed systems

Tools

CuDNN

TensorRT

NCCL

Horovod

CUDA toolkit

MPI

Job description

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement.

This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC’s technology and trading capabilities.

Your Core Responsibilities:

• The opportunity to be in a brand new position in a growing team
• Develop large-scale distributed training pipelines to manage datasets and complex models
• Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems
• Develop libraries to improve the performance of machine learning frameworks
• Maximize performance in training and inference using GPU hardware and acceleration libraries
• Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions
• Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining
• Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs
• Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities
• Dig into the internals of open-source ML tools to extend their capabilities and improve performance

Your Skills and Experience:

• 5+ years of experience in machine learning with a focus on training or inference systems
• Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus
• Strong engineering skills, including Python, CUDA, or C++
• Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
• Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)
• Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL)
• Exposure to cloud platforms and orchestration tools
• A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus

About Us

IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.