Machine Learning Engineer

About the role

The engineer builds pipelines that convert raw satellite imagery into well-labelled data and develops models from it. The work underpins the quality, speed and traceability of geospatial and machine learning products.

What you will do

• Build pipelines for large geospatial imagery and metadata, moving data between annotation, storage and training systems
• Track data lineage and versioning so labels trace back to source images, guidelines and annotators
• Develop, adapt and deploy models that propose annotations and reduce manual labelling effort
• Operate production inference pipelines and evaluate model performance against labelled data
• Use model feedback to decide which imagery to label next
• Collaborate with domain experts, annotation partners and machine learning and software teams

What they look for

• Five or more years in machine learning engineering, data engineering, backend engineering or a related technical role
• Experience deploying models to production with batch or real-time inference pipelines and version management
• Experience building services on a major cloud platform, including compute, databases, storage and access management
• Experience with workflow orchestration for data or ML pipelines, containerized services, CI/CD and infrastructure-as-code
• Strong Python development skills and a relevant degree or equivalent experience

Nice to have

• Experience with Vertex AI, including Vertex AI Pipelines