Senior MLOps Engineer – Computer Vision & AI

Senior MLOps Engineer - Computer Vision & AI The Opportunity We’re looking for an experienced Senior MLOps Engineer to build and maintain the infrastructure that takes AI and Computer Vision models from R&D into production. You’ll ensure models run reliably at scale in the cloud and efficiently on edge devices, including NVIDIA Jetson platforms. This is a hands-on role covering distributed training, model optimisation, containerisation, CI/CD and production monitoring. Working alongside AI developers and software engineers, you’ll help turn advanced AI research into robust, deployable products while influencing the architecture and development of the ML platform. The Technology The team develops advanced Computer Vision and deep learning systems, including CNNs, Vision Transformers and emerging neuroscience-inspired AI. The ML platform supports the full lifecycle, from distributed training and experiment tracking through to inference optimisation, deployment and monitoring across cloud and edge environments. Key Responsibilities - Build and maintain distributed ML training pipelines. - Implement experiment tracking and model registries. - Optimise models for inference using acceleration and quantisation techniques. - Develop containerised deployments for cloud and edge platforms. - Build CI/CD pipelines for automated testing, building and deployment. - Implement production monitoring, metrics and alerting. - Manage edge deployment infrastructure for GPU-accelerated video analytics. - Develop ML workflow orchestration, event-driven processing and data versioning. - Work with AI developers, engineers and customers to deploy reliable production AI systems. - Contribute to infrastructure architecture, technical planning and engineering best practices. Essential Skills and Experience MLOps and Infrastructure - Experience with ML experiment tracking and model registries, such as MLflow, Weights & Biases, Neptune or ClearML. - Distributed training experience using Ray, DeepSpeed, Horovod, PyTorch FSDP or similar. - Model inference optimisation using TensorRT, ONNX Runtime, OpenVINO, quantisation or pruning. - Strong Docker and containerisation skills, including multi-architecture builds. - Experience building ML CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, CircleCI or ArgoCD. - Familiarity with monitoring tools such as Prometheus, Grafana, Datadog or New Relic. Software Engineering - Expert Python development skills. - REST API development using FastAPI, Flask, Django or similar. - Strong engineering practices, including Git, automated testing and code review. - Linux administration and shell scripting. - Familiarity with PostgreSQL or other relational databases. Machine Learning - Understanding of deep learning workflows, preferably using PyTorch. - Experience with Computer Vision models and inference pipelines. - Familiarity with GPU computing and CUDA. - Experience delivering production AI systems. Desirable Skills and Experience - Edge AI: NVIDIA Jetson, Raspberry Pi, Intel NCS or Coral TPU. - Video analytics: NVIDIA DeepStream, GStreamer, FFmpeg and real-time video pipelines. - Workflow orchestration: Metaflow, Kubeflow Pipelines, Airflow, Prefect or Dagster. - Streaming systems: Apache Kafka, Apache Pulsar, Redis Streams or RabbitMQ. - Model serving: Triton Inference Server, Ray Serve, TorchServe, BentoML or similar. - Container orchestration: Kubernetes, Amazon ECS or similar. - Data and optimisation: DVC, LakeFS, Delta Lake, feature stores or hyperparameter optimisation tools. - Infrastructure and compute: Terraform, Ansible, GPU clusters, HPC or distributed training. - Experience with aerial, satellite or ISR imagery. - Defence, government or national security experience. Education and Security An MSc or PhD in Computer Science, Computer Vision, AI, Machine Learning, Robotics or a related discipline is desirable. Equivalent commercial experience will also be considered. Candidates must be eligible to obtain UK security clearance, with BPSS required as a minimum standard to achieve and SC clearance or higher desirable. What’s on Offer? - Ownership of infrastructure supporting advanced AI and Computer Vision. - Involvement across the ML lifecycle, from distributed training to edge deployment. - The opportunity to influence technical architecture and direction. - Collaboration with experienced AI developers and software engineers. - Complex technical challenges across model optimisation, GPU acceleration and production deployment. Employment Details Full-time, permanent. Contract opportunities may also be available. Recruitment is ongoing, with a streamlined interview process.