Uniting Ambition
MLOps Engineering Manager

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MLOps Engineering Manager
£100,000 - £120,000+ DoE
Hybrid | London | 2 x weekly office visits
Permanent
The Business
Join a globally recognised brand with a legacy of excellence and a track record of shaping its industry.
While its heritage is well established, the organisation is firmly focused on the future, making major investments across technology, data, and AI to accelerate innovation at scale.
As part of this journey, they are now seeking a highly capable technical leader to help support their next phase of growth and lead complex transformation initiatives.
The Role
This is a combination of strong technical leadership, architectural ownership and delivery responsibility of ML systems (from backend infrastructure through to frontend integration).
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.
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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.
There is an ongoing migration from MLflow to AWS SageMaker, so you will be working closely with data scientists, engineers and cross-functional stakeholders to deliver this.
You will also be responsible for MLOps delivery from predictive maintenance, fault detection, and component lifecycle optimisation, while leading and mentoring a team of engineers.
You will also be working with 5-10 engineers with a slightly higher focus on people leadership (approximately 60/40 split - people leadership / hands-on).


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About you
- 10+ years in Software, Data, or ML Engineering
- 5+ years as a Tech Lead, managing teams of 5+, owning end-to-end technical delivery
- Proficiency with Python and MLflow
- Strong AWS/cloud-native experience (ideally with SageMaker exposure)
- React frontend proficiency
- Docker, Kafka, and large-scale data systems (e.g. Spark) experience
- Strong leadership presence and senior stakeholder communication skills
If you have the technical expertise, leadership experience and ambition to make an impact at scale, please apply now.
We'd be delighted to discuss the opportunity with you.
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