Machine Learning Engineer - #2179078

SR2


Date: 53 minutes ago
City: London
Salary: £500 - £625 / day
Contract type: Full time
SR2

Machine Learning / ML Ops Engineer
Outside IR35: £500 - 625 p/d
Active SC Clearance Required
4 days a week into East London
6 months initial contract, long term programme

The Role
We're looking for a Senior MLOps Engineer to build and run the infrastructure that takes machine learning models from research into production. You'll work alongside AI developers, software engineers and technical leadership to turn R&D into reliable, deployable products in the cloud and on edge hardware. The work is for a long-term programme in the defence and security sector.

This is a hands-on role, and you'll have real influence over the architecture of the ML platform.

What you'll do

  • Design and maintain ML training pipelines, including distributed training at scale
  • Build experiment tracking, model registry and data versioning capability
  • Optimise models for production and edge deployment
  • Containerise ML workloads, including multi-architecture builds for cloud and edge targets
  • Implement CI/CD for ML systems
  • Build monitoring and observability for models in production
  • Orchestrate ML workflows and event-driven pipelines

What you'll bring

  • Strong commercial MLOps or ML engineering experience, taking models from R&D into production
  • Distributed training frameworks (e.g. Ray, DeepSpeed, PyTorch Lightning)
  • Experiment tracking and model registries (e.g. MLflow or similar)
  • Model optimisation (e.g. ONNX, TensorRT, quantisation)
  • Docker and containerised deployment
  • CI/CD tooling (e.g. GitHub Actions, GitLab CI or similar)
  • Monitoring and observability (e.g. Prometheus, Grafana)
  • Active SC clearance

Nice to have

  • Edge AI deployment, ideally NVIDIA Jetson and DeepStream
  • Computer vision or video pipelines (e.g. GStreamer)
  • Kubernetes, Kubeflow, Metaflow or similar orchestration tools
  • Kafka or other event-driven architectures
  • Data versioning tools (e.g. DVC, DeepLake)
  • Experience with imagery, geospatial or sensor data
  • Previous defence, government or security-sector programmes
  • MSc or PhD in Computer Science, ML or a related field, or equivalent commercial experience

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