Summary
✨ AI‑Generated
Build large-scale systems for training and deploying machine learning models in a performance-critical environment. You will develop distributed training pipelines, optimize GPU-accelerated workloads, and build low-latency inference systems while collaborating across research, hardware, and software disciplines.
Highlights
Work at the intersection of advanced machine learning and quantitative trading, collaborating with researchers, hardware specialists, and software engineers on large-scale systems and high-performance ML infrastructure.
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 modelsBuild and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systemsDevelop libraries to improve the performance of machine learning frameworksMaximize performance in training and inference using GPU hardware and acceleration librariesDesign scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictionsCollaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retrainingPartner with HPC specialists to optimize workflows, improve training speed, and reduce costsEvaluate and roll out third-party tools to enhance model development, training, and inference capabilitiesDig 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 systemsHands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plusStrong engineering skills, including Python, CUDA, or C++Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAXProficiency 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 toolsA 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.
