Senior MLOps Engineer

You will develop and optimise the infrastructure that moves AI and computer vision models from research to reliable production. You’ll bridge research and operations to enable efficient training, stable deployment and thorough monitoring. The role is hands-on across distributed training, model registries, containerised deployments and edge-accelerated inference. You’ll work with cloud and edge devices, including NVIDIA Jetson systems, to deliver robust AI systems for demanding environments. This is a cross-functional, customer-facing senior position with real-world impact and growth opportunities.

• Develop distributed training pipelines for large-scale model development
• Implement and manage ML experiment-tracking and model-registry infrastructure
• Optimise production-ready models via inference acceleration, quantisation and pruning
• Build containerised deployment pipelines for cloud, x86 and edge architectures
• Develop and maintain CI/CD pipelines for ML systems
• Manage GPU-accelerated edge deployment and video-analytics infrastructure
• Develop event-driven processing systems
• Collaborate with AI Engineers, Software Engineers and customers to productionise models
• Contribute to technical planning, architecture decisions and best practices

• Strong Python development skills
• Experience with ML experiment tracking and model registries (MLflow, Weights & Biases, Neptune, ClearML or similar)
• Experience with distributed training frameworks (Ray, DeepSpeed, Horovod, PyTorch FSDP)
• Hands-on experience optimising inference with TensorRT, ONNX Runtime, OpenVINO, quantisation or pruning
• Strong Docker and containerisation skills (multi-stage or multi-architecture builds)
• Experience building CI/CD pipelines for ML systems
• Experience with monitoring/observability tools (Prometheus, Grafana, Datadog or similar)
• Linux administration and shell scripting
• Strong software engineering practices (Git, testing, code reviews)
• Experience delivering AI/ML systems into production

• collaboration
• customer-facing communication
• problem-solving
• MLflow
• Weights & Biases
• Neptune