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Onric

MLOps / DevOps Infrastructure Engineer

City of Edinburgh
Posted about 16 hours ago
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Application / Mid-Senior

MLOps / DevOps Infrastructure Engineer

You will make the research and product stack dependable. Onric needs infrastructure that can run CAD jobs, model jobs, simulation jobs, and data pipelines without turning every experiment into a cost or reliability surprise.

What you will do

  • Build infrastructure for model serving, simulation jobs, and secure data storage.
  • Operate LLM and robotics-model deployment pipelines.
  • Implement CI/CD, observability, experiment tracking, and cost controls.
  • Keep CAD, simulation, and model jobs reliable in production.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Strong

Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Expected outcomes

  • Keep LLM serving, frontier API routing, CAD jobs, and simulation jobs reliable.
  • Build secure data pipelines.
  • Support repeatable experiments and model evaluation workflows.
  • Reduce infrastructure cost while maintaining performance and uptime.

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Skills Required

  • Docker, Kubernetes, and CI/CD.
  • GPU serving and inference optimisation.
  • Job queues, observability, and experiment tracking.
  • Cloud infrastructure, secrets management, and security.
  • Cost control and performance monitoring.
  • Data storage, versioning, and model deployment workflows.
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Skills

Docker
Kubernetes
CI/CD
GPU Serving
Inference Optimisation
Job Queues
Observability
Experiment Tracking
Cloud Infrastructure
Secrets Management
Security
Cost Control
Performance Monitoring
Data Storage
Versioning
Model Deployment

Location

City of Edinburgh, Scotland, United Kingdom

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