Machine Learning Engineer

23 Hours ago • 5 Years + • $175,000 PA - $250,000 PA

Job Summary

Job Description

As a Machine Learning Engineer, you will be responsible for building systems to train and deploy large-scale ML models across global operations. You will collaborate with researchers and engineers to build robust solutions, maximizing the potential of GPU acceleration and distributed computing. Your work will influence trading strategies by accelerating experimentation. Responsibilities include developing distributed training pipelines, building low-latency inference pipelines, optimizing performance, designing scalable model frameworks, collaborating on ML experiments, and evaluating third-party tools.

Must have:

5+ years of experience in machine learning with focus on training or inference systems
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
Experience with distributed training for scaling ML workloads
Exposure to cloud platforms and orchestration tools

Good to have:

Hands-on experience with real-time, low-latency ML pipelines
A track record of contributing to open-source projects

6 skills required

6 skills required for this role

Add these skills to join the top 1% applicants for this job

tensorflow

python

pytorch

data-science

cuda

innovation

Job Details

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:

5+ 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