ML Data & Platform Engineer

We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster.

This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix.

What you'll do

• Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models
• Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale
• Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production
• Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency
• Implementing observability (monitoring, logging, alerting) across data pi