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Machine Learning Engineer

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We are working with a leading healthcare AI pioneer transforming drug development through cutting-edge artificial intelligence and world-leading multi-modal generative AI foundation models.
The Opportunity
We're seeking an exceptional Software / Machine Learning Engineer to join their central London office, working on novel Foundation Models. This is a rare opportunity to work at the intersection of advanced software engineering and frontier AI research, building systems that directly enable breakthroughs in drug development and patient care.
Your work will directly accelerate research velocity, enabling the team to iterate faster, experiment more effectively, and push the boundaries of what's possible in AI-driven healthcare.
Role Requirements
Core
- Strong general software engineering skills: clean, tested Python, comfortable owning systems end to end
- Hands-on experience with large, messy datasets: cleaning, joining, versioning, and validating data at scale
- Experience making ML training and inference run efficiently on very large data: caching, data loading, memory management, cross-node communication
- Working knowledge of PyTorch and/or JAX training loops
- Experience running workloads on HPC or multi-node GPU clusters (e.g. Slurm, distributed training)
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.
Bonus points
- Prior work with health records, single-cell / cytometry data, or time-series
- Prior experience working with Tabular data / datasets
- Comfortable across the stack: data pipelines, model training, and evaluation — rather than specialising in one
- Experience in a startup or small, fast-moving research team; ships without heavy process
Nice to haves
- A biology or clinical background, or a demonstrated interest in learning the domain
- Familiarity with secure data environments (NHS TREs, data governance, de-identification)
Why This Role is Different
- Impact: Your work will directly accelerate research that's transforming drug development and saving lives. The tools you build will enable breakthroughs in understanding and treating complex diseases.
- Technical Challenge: Work on genuinely novel problems at the frontier of ML engineering. You'll tackle challenges around scale, complexity, and domain-specific constraints that few engineers ever encounter.
- Cutting-Edge Research: Collaborate daily with world-class researchers pushing the boundaries of AI in healthcare. You'll be exposed to the latest developments in foundation models, multi-modal learning, and medical AI.
- Autonomy & Ownership: Take ownership of critical systems and make architectural decisions that shape the technical direction. Your input will directly influence research capabilities and velocity.
- Fast-Paced Growth: Join during a period of rapid scaling with opportunities to grow your skills, take on increasing responsibility, and help shape the engineering culture.


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Location & Work Environment
This role is approx 4 days a week based in their London office, where the majority of the technical team, including ML researchers and engineering teams, are located. You'll be at the heart of R&D activities, with daily opportunities for face-to-face collaboration, whiteboard sessions, and rapid iteration with the team.
They foster a culture of intellectual curiosity, technical rigor, and collaborative problem-solving. The environment balances the urgency and pace of a fast-growing startup with the thoughtfulness and precision required for building foundation AI models that must meet the highest standards of accuracy and reliability.
“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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