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Machine Learning Engineer

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Machine Learning Engineer, London
I'm working with a highly technical organisation, a new client of ours and a global hedge fund, that wants a Machine Learning Engineer focused on the systems that make ML work, not on building models.
What you'll be working on:
- Trialling emerging ML frameworks and hardware before most people have heard of them
- Speeding up training and inference across a very large GPU estate
- Tracking down tricky bottlenecks across compute, networking and storage
- Partnering with engineers around the business to push their ML workloads further
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 makes the opportunity interesting:
- Time to experiment is built into the role
- Access to GPU resources few organisations can match
- Hiring is based on PyTorch depth and solid engineering, not titles
- Research labs or major tech firms are a natural background, but not a requirement
- A long term technical career path with no push into management


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This would suit someone who loves working out why an ML job behaves the way it does, then making it quicker. Earning potential of an additional £100k to £200k.
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