Senior MLOps Engineer, ISR

📋 Description

• Build training, evaluation and packaging pipelines that take a model from experiment to versioned
• Deploy and serve models on Kubernetes with GPUs, in the cloud and on-prem, including air-gapped
• Package models, weights and dependencies so they install and upgrade offline.
• Manage GPU compute: scheduling, drivers, utilization and cost, across cloud and on-prem hardware.
• Track data, experiments and model lineage, so any result can be reproduced and audited.
• Monitor models in production for performance, drift and failures, without relying on outside

🎯 Requirements

• Senior hands-on engineer (not an engineering manager or architect role).
• Proven experience deploying ML models to production and running them there, not only training them.
• Strong Python, and comfort reading and changing ML code (PyTorch or similar).
• Hands-on Kubernetes and containers, including GPU workloads.
• Infrastructure as code and CI/CD for ML (for example Terraform, Helm, GitHub Actions).
• Daily use of AI tools in engineering work, beyond chat: generating and reviewing code

🎁 Benefits

• Our benefits are designed to support your health and wellbeing, at work and beyond. We keep