Senior Machine Learning Engineer (Platform)

📋 Description

• Build and operate ML pipelines - Own the training, evaluation, and deployment pipelines end-to-end
• Automate the path to production - Build CI/CD for models, artefact and model registries
• Keep production models healthy - Implement monitoring, alerting, and drift and data quality checks
• Run distributed training infrastructure - Manage GPU clusters and scheduling, keep jobs efficient
• Ship reliable serving infrastructure - Deploy and scale inference services that handle spiky load
• Remove friction for the ML team - Improve the tooling and workflows ML engineers use daily, and

🎯 Requirements

• Solid hands-on experience building and operating ML training pipelines, model serving, and
• Strong Python, and working knowledge of PyTorch (or equivalent) - enough to debug a training job
• Practical experience with distributed training and GPU infrastructure, including scheduling
• Experience in the cloud (AWS, GCP, or Azure), container orchestration (Kubernetes, Docker), and
• Experience with production model monitoring, data quality frameworks, and preparing training data
• Sound engineering judgement - you write maintainable code, think about failure modes, and know when

🎁 Benefits

• Competitive salary
• Meaningful ESOP
• Fully Flexible Work Environment. We have a fully stocked office (and an impressive snack
• Regular office events
• The real benefit is working on a genuinely complex, innovative and industry-leading product, making