ML Systems Engineer: Scalable Training & Inference

IMC Trading; New York (NY); On-site; USD 175,000 - 250,000; Full time

Job summary

IMC is seeking Machine Learning Engineers to build and optimize large-scale training pipelines and real-time inference systems that power trading platforms across global markets. You will collaborate with researchers, hardware specialists and software engineers to accelerate experimentation, tuning, and deployment, leveraging GPU acceleration and distributed computing.

Across ML Research and ML Performance Engineering, you will advance frameworks, infrastructure, and tooling to deliver

Qualifications

• 3+ years of experience in machine learning, with a focus on training or inference systems.

Responsibilities

• Develop large-scale distributed training pipelines for complex datasets and models.
• Partner with quantitative researchers to automate ML experiments, hyperparameter tuning and model 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 predictions in production systems.
• Maximise performance in training and inference using GPU hardware and acceleration libraries.

Skills

Python

ML fundamentals

Systems mindset

Collaboration

Distributed training

GPU performance

Job description

IMC is seeking Machine Learning Engineers to build and optimize large-scale training pipelines and real-time inference systems that power trading platforms across global markets. You will collaborate with researchers, hardware specialists and software engineers to accelerate experimentation, tuning, and deployment, leveraging GPU acceleration and distributed computing.

Across ML Research and ML Performance Engineering, you will advance frameworks, infrastructure, and tooling to deliver