Machine Learning Engineer
Salary not listed • Hong Kong, Hong Kong; Sydney, Australia • Full-time
Posted 4mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
Hong Kong, Hong Kong; Sydney, Australia
Also open in Amsterdam, Netherlands; London, United Kingdom
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
IMC is seeking Machine Learning Engineers to build and deploy large-scale ML models across its global operations. You will collaborate with researchers, hardware specialists, and software engineers to create robust systems that leverage GPU acceleration and distributed computing. This role is crucial for accelerating the cycle from research idea to live trading strategy, offering a unique opportunity to solve complex problems at the intersection of advanced machine learning and trading. The team focuses on two main areas: ML Research Engineering, which involves building systems and frameworks for model training and evaluation at scale, and ML Performance Engineering, dedicated to optimizing ML workloads for maximum efficiency, particularly through GPU and low-level systems optimization. While there's overlap, you'll bring expertise in at least one of these areas and work closely with a global team.
Responsibilities
- Develop large-scale distributed training pipelines for complex datasets and models.
- Automate ML experiments, hyperparameter tuning, and model retraining in partnership with researchers.
- Optimize workflows, training speed, and compute costs with HPC specialists.
- Build and optimize low-latency inference pipelines for real-time predictions.
- Maximize training and inference performance using GPU hardware and acceleration libraries.
- Extend and improve machine learning frameworks and open-source tools for enhanced performance.
- Design scalable model infrastructure for high-volume trading data and real-time predictions.
- Evaluate and implement third-party tools to improve model development, training, and inference.
Requirements
- 3+ years of experience in machine learning, focusing on training or inference systems.
- Proficiency in production software engineering with Python, testing, and system ownership.
- Strong understanding of machine learning fundamentals, including model behavior, correctness, and performance.
- A systems mindset with a data-driven approach to performance, scale, and reliability.
- Excellent collaboration skills, with the ability to explain technical decisions and adapt approaches.
- Depth in distributed training, large-scale systems, or GPU performance optimization.
- Experience with production inference systems and low-latency prediction pipelines.
- Knowledge of numerics and correctness at scale, including low-precision effects and optimizations.