Machine Learning Engineer

IMC is a leading trading firm known for advanced, low-latency technology and world-class execution capabilities in financial markets.
Machine Learning
Senior Software Engineer
Contact Company
5+ years of experience
Finance · AI

Description For Machine Learning Engineer

As a Machine Learning Engineer at IMC, you'll be at the forefront of building systems for training and deploying large-scale ML models across global operations. This role offers a unique opportunity to solve problems at the intersection of advanced machine learning and high-frequency trading.

Your core responsibilities will include:

  • Developing large-scale distributed training pipelines
  • Building and optimizing low-latency inference pipelines
  • Developing libraries to improve ML framework performance
  • Maximizing performance using GPU hardware and acceleration libraries
  • Designing scalable model frameworks for high-volume trading data
  • Collaborating with researchers to automate ML experiments
  • Partnering with HPC specialists to optimize workflows
  • Evaluating and implementing third-party tools
  • Extending capabilities of open-source ML tools

Required skills and experience:

  • 5+ years of experience in machine learning, focusing on training and inference systems
  • Strong engineering skills in Python, CUDA, or C++
  • Knowledge of deep learning frameworks (PyTorch, TensorFlow, JAX)
  • Proficiency in GPU programming for ML acceleration
  • Experience with distributed training for scaling ML workloads
  • Exposure to cloud platforms and orchestration tools

IMC offers a dynamic work environment across offices in the US, Europe, and Asia Pacific. The company is known for its entrepreneurial spirit, exceptional culture, and commitment to giving back. This role provides an opportunity to work on cutting-edge technology in financial markets, contributing to IMC's continuous innovation and growth.

Last updated 7 days ago

Responsibilities For Machine Learning Engineer

  • 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

Requirements For Machine Learning Engineer

Python
  • 5+ years of experience in machine learning with a focus on training and inference systems
  • Strong engineering skills, including Python, CUDA, or C++
  • Knowledge of deep 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

Interested in this job?

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