Summary

The ML Data & Platform Engineer will build data pipelines and the infrastructure supporting speech AI model training, evaluation, and production serving. The role is hybrid, with 2–3 designated office days each week, and focuses on Python, SQL, Docker, Kubernetes, distributed systems, and MLOps.

Responsibilities

• Design scalable pipelines for training datasets
• Develop web scraping and data acquisition systems
• Operate infrastructure for model deployment and evaluation
• Optimise gpu utilisation and training efficiency
• Implement monitoring, logging, and alerting
• Troubleshoot distributed data and ml systems
• Improve data quality and mlops practices