Real-Time ML Engineer for GPU-Accelerated Trading

IMC Trading; Sydney; Hybrid; AUD 90,000 - 130,000; Full time

Job summary

IMC Trading is seeking a Machine Learning Engineer to develop distributed training pipelines and optimize inference systems. This role involves collaboration with researchers and engineers to enhance trading strategies through advanced machine learning.

Ideal candidates should possess over 3 years of experience in machine learning, coupled with strong programming skills in Python or C++. The position emphasizes GPU programming and real-time data handling.

Qualifications

• 3+ 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++.

Responsibilities

• Develop large-scale distributed training pipelines for datasets and complex models.
• Build and optimize low-latency inference pipelines for real-time predictions.
• Collaborate with quantitative researchers to automate ML experiments.

Skills

Machine learning

Python

CUDA

C++

GPU programming

Real-time ML pipelines

Distributed training

Tools

PyTorch

TensorFlow

JAX

CuDNN

TensorRT

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

• 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

• 3+ 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 global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.