ML Engineer: Real-Time Distributed Training & Inference

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

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.