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Lead AI Engineer (Dubai)

London
Posted about 18 hours ago
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This role requires relocation to Dubai

I’m partnering with a fast-growing technology company in Dubai to hire a Lead AI Engineer for a highly technical, hands-on leadership role.

This isn’t a typical “AI Engineer” position. We’re looking for someone whose foundations are genuinely in AI/ML, data science and research — someone who understands the mathematics behind the models, can read cutting-edge research and turn it into working software, but who has also developed the engineering breadth to build and ship complete products.

A PhD / significant academic research background in AI, Machine Learning, Computer Science or a closely related discipline is essential for this search.

What you’ll be doing

  • Lead forward-looking AI/ML research and development from 0 → 1
  • Build, train, validate and calibrate ML models — not simply integrate model APIs
  • Turn new research papers and emerging techniques into working prototypes and production systems
  • Work across foundation models, agents, causal inference, real-time ML and streaming analytics
  • Take ideas from research through to production across models, data infrastructure, backend services and product interfaces
  • Set the technical and architectural direction for ambitious AI initiatives
  • Remain highly hands-on — coding, experimenting and prototyping
  • Help build and mentor a high-performing AI/engineering team

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.

P

Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your 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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It 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.

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Strong

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.

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Strong

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 we’re looking for

  • PhD / strong research background — essential
  • Deep foundations in Machine Learning / Data Science / AI
  • 8+ years’ experience across AI, ML and engineering with evidence of having built and shipped real ML models
  • Strong Python and modern ML frameworks such as PyTorch / TensorFlow
  • Experience with distributed data technologies such as Spark, Kafka, Snowflake or Databricks
  • Ability to understand and implement ideas from academic AI/ML research
  • Strong engineering capability across production-grade systems
  • Experience taking AI/ML research from experimentation into scalable products
  • Strong product mindset — you care about how what you build is actually used
  • Comfortable operating as a senior individual contributor, not simply managing from a distance

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Published research, open-source AI contributions and experience within fintech would be particularly interesting.

This is a rare opportunity for someone who wants to sit at the intersection of AI research, machine learning, engineering and product, with genuine ownership over what gets built. If your career started closer to models and research and expanded into engineering — rather than the other way around — I’d particularly like to hear from you.

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Jessica, London

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Skills

Machine Learning
Artificial Intelligence
Python
PyTorch
TensorFlow
Spark
Kafka
Snowflake
Databricks
Causal Inference
Streaming Analytics
Data Science
Distributed Data Technologies
Model Calibration
Software Engineering
Research Implementation

Location

London, England, United Kingdom

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