ML Data & Platform Engineer

Job summary

The ML Data & Platform Engineer is responsible for managing the infrastructure that supports speech AI models, focusing on data pipelines and model deployment. Key responsibilities include designing scalable data pipelines, developing web scraping solutions, and optimizing production infrastructure for reliability and efficiency, utilizing technologies such as Python, SQL, Docker, and Kubernetes.

Qualifications

• Strong proficiency in Python and SQL
• Hands-on experience with Docker and Kubernetes
• Experience building data pipelines and ETL/ELT processes
• Understanding of the ML lifecycle from data to model serving
• Experience with data quality practices and observability
• Ability to design resilient, scalable architectures
• MLOps experience in model serving and training optimisation
• Self-starter mentality for problem identification and resolution

Responsibilities

• Designing, building, and maintaining scalable data pipelines
• Developing and maintaining web scraping and data acquisition solutions
• Building and operating infrastructure for model deployment and evaluation
• Optimising infrastructure for iteration speed and production reliability
• Implementing observability across data pipelines and ML systems
• Troubleshooting complex issues across distributed systems
• Continuously improving data and MLOps practices

Skills

Relocation