Senior MLOps Engineer

• Turning ML models into production-ready, customer-facing services
• Creating CI/CD pipelines for models, not just code
• Designing low-latency, high-availability inference infrastructure
• Monitoring live models for drift, performance drops, and failures
• Scaling ML systems as pilot customers onboard
• Working closely with AI, data, and software engineers to ship reliably

You don’t need to tick every box, but you will have real experience running ML in production.

• 4+ years in MLOps, ML Engineering, or ML-heavy DevOps roles
• Strong Python and hands-on ML framework experience (PyTorch, TensorFlow, etc.)
• Experience deploying and serving ML models in production
• Containerisation and orchestration (Docker, Kubernetes or ECS)
• CI/CD for ML workflows

• Model monitoring & observability (Prometheus, Grafana, Datadog)
• A/B testing or canary deployments for ML models
• Startup or scale-up experience
• Work on real-time behavioural AI used in authentication
• High ownership, you’ll shape how ML is run across the company for clients
• Direct impact as we move into live customer deployments
• Hybrid working (Manchester-based)
• Join at a pivotal growth moment, not after everything is already decided