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Senior Machine Learning Engineer

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Machine Learning Engineer – London (Hybrid)
I'm working with a highly technical organisation in London that is looking for a Machine Learning Engineer who loves making things go faster.
This is an engineering focused role: take new ML technology, push it hard and find out what really works.
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.
Start with a chat, not a search bar
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.
What you'll be working on:
- Getting hands on with new hardware and frameworks early
- Improving the speed and scale of ML workloads
- Solving performance problems that don't have an obvious answer
What makes the opportunity interesting:
- Exploration is a core part of the job, not a side project
- Serious compute and genuinely hard engineering problems
- Strong PyTorch skills valued over any particular background
- A path to stay deeply technical


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This would suit someone who gets a bigger kick from shaving milliseconds off a workload than from building the model itself.
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