Machine Learning Engineer

As a team, our Machine Learning Engineers broadly work across two areas: ML Research Engineering, focused on the systems and frameworks researchers use to train, evaluate and iterate on models at scale; and ML Performance Engineering, focused on making ML workloads execute as efficiently as possible, typically through GPU and low-level systems optimisation. These aren't rigid tracks, and there is overlap between them. You will bring depth of expertise in at least one of these focus areas and collaborate closely with global team members.

• Develop large-scale distributed training pipelines that manage complex datasets and models.
• Partner with quantitative researchers to automate ML experiments, hyperparameter tuning and model retraining.
• Work with HPC specialists to optimise workflows, improve training speed and reduce compute cost.