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Staff Machine Learning Scientist

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Staff Machine Learning Scientist | Core ML | UK (Hybrid)
Location: London
Type: Permanent
Salary: £100,000–£120,000 per annum
The Company
Our client is an established, tech-driven digital platform with an international footprint and millions of active users. Operating independently as part of a global group, they combine an agile, engineering-led culture with the backing and resources of a major parent business.
The Role
This is a high-visibility opportunity for an experienced Machine Learning Scientist to join a newly formed Core ML team and shape technical direction from day one. Reporting directly to the new Senior ML Engineering Manager, you will work closely with leadership to establish core architecture and team standards.
As a Staff Machine Learning Scientist, you will build foundational models that serve multiple engineering and product verticals—focusing on representation learning, visual embeddings, and generalized automated classifiers.
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.
In this role, each Machine Learning Scientist on the team will look to you for technical strategy, complex engineering leadership, and mentorship while you collaborate directly with Product Managers, ML Engineers, and Data Scientists.
What You'll Do
- Design, build, and deploy ML systems addressing multi-faceted platform challenges.
- Develop and fine-tune models for representation learning, vision tasks, and core classification, scaling them as shared services.
- Partner with senior stakeholders to define technical roadmaps for automated content understanding, risk/trust systems, and personalization.
- Drive large-scale, end-to-end experiment design—from initial hypothesis to production evaluation and business impact assessment.
- Evaluate emerging research, contribute to long-term data strategy, and foster engineering best practices across teams.
- Lead technical whiteboarding, architectural reviews, and roadmap planning sessions.
- Translate complex machine learning concepts into actionable strategy for cross-functional leadership.


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What You'll Bring
- A track record of shipping and scaling ML models with measurable commercial impact
- Deep ML knowledge applied in production, using PyTorch, TensorFlow or Transformers
- Strong, production-quality Python, plus solid data engineering and MLOps foundations
- Experience owning ML initiatives end to end, working through ambiguity, and mentoring others
- Strong collaboration skills across multi-functional teams
- Real curiosity about AI and how it can improve the way you work
Nice to Have
- NLP, image classification, deep learning or LLM experience
- A/B testing and experiment design
- Experience building platform-style or shared ML systems
- Databricks and PySpark
- AWS, GCP or Azure
Interested? If you're an experienced Machine Learning Scientist ready to take on this challenge, we'd love to hear from you.
Get in touch: max@neartechsearch.com
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