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About the Role
A growing AI company is looking for a technically strong Research Scientist or Engineer to join early and help build systems that get smarter about the people using them, learning from how someone interacts with the product and using that to shape the experience they get. The team blends machine learning, applied research, and product-facing engineering, and is led by a founder with a solid research background.
You’d be joining at a formative stage, with real input into how the product’s core technology takes shape.
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 Work Involves
- Building out ways to measure whether the system is responding appropriately given what it knows about a given user
- Turning real usage and feedback into structured signals the model can learn from
- Running training experiments aimed at improving response quality based on human feedback
- Digging into cases where the system gets it wrong — misreads a user, holds onto outdated info, or responds inconsistently
- Weighing in on technical decisions as the product architecture comes together


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Ideal Background
- A few years of hands-on experience shipping ML or AI-driven products
- Exposure to model fine-tuning, evaluation work, or working with human feedback data
- Comfortable in Python, with practical experience in common deep learning tooling
- Self-starter who’s happy figuring things out without a lot of structure
Compensation
Competitive salary + equity.
Contact Information
Please feel free to reach out to Charles Duran
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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