Harnham
MLOps Engineer

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Senior MLOps Engineer
London (Hybrid) | £75,000 - £85,000 + Bonus + Benefits
This is an opportunity to take ownership of the infrastructure powering a growing AI platform. You'll work across machine learning, NLP, and emerging AI technologies, helping build scalable systems that support real-world impact.
The Company
A growing AI and data consultancy helping organisations use data and machine learning to improve decision-making and deliver better outcomes. They are investing heavily in their AI platform and expanding their engineering capability.
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.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour 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.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
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.
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.
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.
The Role
- Own and develop the MLOps infrastructure supporting AI services.
- Build and maintain orchestration pipelines using Dagster, Airflow, or Prefect.
- Deploy and manage ML workloads on Kubernetes and cloud platforms.
- Implement CI/CD, observability, and monitoring across production systems.
- Develop infrastructure using Terraform, Bicep, or similar IaC tools.
- Work closely with Data Scientists, ML Engineers, and AI teams to scale deployments.


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Your Skills & Experience
- Strong Python software engineering skills.
- Commercial MLOps experience in production environments.
- Hands-on Kubernetes expertise.
- Experience with workflow orchestration platforms.
- Infrastructure as Code and CI/CD experience.
- Understanding of production ML, NLP, or AI systems.
Desired Skills and Experience
- MLOps, CI/CD, Azure, Python
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