- Pay
- £45–65k
- Where
- Newcastle, Tyne and Wear, GB · GB · Remote · Remote
- Level
- Mid
Step into this Machine Learning Operations Engineer role and build something that matters in AI & Technology.
AI models are easy to prototype and hard to run.
The gap between a notebook that works and a system that holds up in production is where most AI companies quietly fail, and it's exactly where this role sits.
This is a fast-growing startup in the AI & Technology space, building tools that depend on models staying fast, stable and correctly versioned once real users show up.
The team is small.
Decisions happen quickly, and nobody is waiting around for a committee to sign off on a deployment pipeline.
If you want ownership over how machine learning actually reaches production, this Machine Learning Operations Engineer position gives you that from week one.
Here's what you'll be doing: Build and maintain CI/CD pipelines for model training, testing and deployment Monitor model performance in production and catch drift before it becomes a problem Design infrastructure for scalable model serving, using containerisation and orchestration tools Work closely with data scientists to turn experimental models into reliable, repeatable systems Automate retraining workflows and manage versioning across datasets, features and models Troubleshoot production incidents and tighten up observability so the next one is easier to catch Here are the skills you'll need: Solid experience with MLOps tooling (MLflow, Kubeflow, or similar) and cloud platforms (AWS, GCP or Azure) Strong Python skills, plus comfort with Docker and Kubernetes in production settings Working knowledge of CI/CD practices and infrastructure as code (Terraform is a plus) A few years' experience supporting machine learning systems beyond the experimentation stage Good judgement under ambiguity.
Startups rarely hand you a finished spec Clear communication with data scientists and engineers who think about problems differently to you Key perks and benefits: £45,000 to £65,000, depending on experience Fully remote working, with flexible hours built around how you work best Equity in the business.
You're building this alongside the founders, not just for them A genuine learning and development budget, not a token gesture Flat structure.
Your ideas reach decision-makers directly, without layers in between Why pursue a career in AI & Technology?
AI & Technology isn't slowing down, and the engineers who keep models running reliably are becoming just as valuable as the ones who build them.
Newcastle has a growing cluster of tech talent and increasingly looks like a smart base for this kind of work, away from the cost and noise of London.
Get good at MLOps now and you'll have your pick of roles for years to come.
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