Senior ML Engineer
Production ML engineers — 7+ years — owning model, serving, evaluation and monitoring end-to-end for GCC AI teams.
Senior ML Engineers in the GCC are working on systems that report directly into a Head of AI or VP of Engineering, ship to production inside their first quarter, and own a stream of work end-to-end. Engineering scaffolding — CI/CD, observability, evaluation harnesses — is usually half-built; you finish it.
Most mandates we see in this band sit inside one of three contexts: PIF portfolio companies and HUMAIN-adjacent teams; G42 portfolio operating companies (Core42, Presight, Inception); and the AI functions inside regional banks and energy majors (Aramco Digital, ADNOC AIQ, Emirates NBD, Mashreq).
What you'll typically own
- Own systems, not tickets. A single Senior ML Engineer typically owns one production system — model, serving, evaluation, monitoring — and is in the conversation when the next system gets scoped.
- Take ML problems from research prototype to production scale on sovereign infrastructure, including non-hyperscaler stacks.
- Build evaluation harnesses, observability, and offline/online metrics that survive the first six months of real traffic.
- Fine-tune and post-train LLMs against domain corpora — RAG, supervised fine-tuning, preference optimisation, inference optimisation.
- Mentor mid-level engineers and partner with platform / data teams on the model serving stack.
Profile fit
Must have
- 7+ years building ML systems in production, not in research.
- Genuine depth in PyTorch or JAX. Comfortable reading recent papers and implementing.
- LLM experience at the engineering layer — fine-tuning, serving, evaluation, retrieval — not just via API.
- MLOps fluency: pipelines, CI/CD for models, monitoring, feature stores.
- Track record shipping ML to real users at scale.
Nice to have
- Experience on sovereign or non-hyperscaler infrastructure (on-prem H100 clusters, Inception, Core42).
- Arabic language capability or prior GCC experience.
- Open-source contributions to ML infrastructure.
- Background in one of: financial services AI, energy / industrial AI, government data.
Indicative package
Total fixed monthly base, tax-free. Housing, transport and school allowances typically add 25–35% on top. Bonus is target, paid annually.
| UAE · AED · per month | KSA · SAR · per month | |
|---|---|---|
| Senior (7–12 yrs) | AED40,000–55,000/mo | SAR38,000–48,000/mo |
| Senior+ (10–15 yrs) | AED55,000–65,000/mo | SAR48,000–55,000/mo |
| Bonus typical | AED15–25% | SAR15–25% |
USD equivalent: approximately $131,000–$212,000 per year before bonus.
Location & corridor
KSA
Riyadh primary, with selective NEOM and Jeddah mandates. Most teams operate on-site 4–5 days; sovereign programmes are typically on-site full-time.
UAE
Abu Dhabi and Dubai. Hybrid is more accessible than KSA — 3 days on-site is typical, fully remote within UAE is occasional for senior ICs.
Visa & relocation
Full sponsorship is standard at this level. Family visa, schooling allowance and health cover are typically included. Spouse work authorisation is straightforward in UAE; KSA depends on the employer and dependant category. Most clients fund a relocation package covering flights, 30–60 days temporary accommodation, and shipping.
Get on our radar for this role.
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Want the market context for this band? Read the GCC market intelligence brief.
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