Job at a Glance
- 📍 Location: Sharjah, Sharjah Emirate, United Arab Emirates
- 🏢 Company: WSP in the Middle East
- 💼 Employment Type: Full-time
- 📊 Seniority: Not Applicable
- 🗂️ Function: Engineering and Information Technology
- 🏭 Industry: Professional Services
- 📅 Date Posted: 2026-08-11
- 🌐 Category: Artificial Intelligence
About the Role & Company
WSP in the Middle East is hiring a Graduate – Artificial Intelligence (Emirati National) in Sharjah, Sharjah Emirate, United Arab Emirates. This is a Artificial Intelligence seat inside a team that’s shaping how the function scales locally. Career-wise, joining a growing team beats a static one; there’s more room to shape scope early. Expect the standard Graduate – Artificial Intelligence (Emirati National) responsibilities plus the flex that comes with a growing team. GCC demand for artificial intelligence skills is still healthy, and Dubai continues to sit at the top of the regional pay bands. It’s a solid entry point for candidates who want regional exposure without giving up ownership of real work — you’re contributing, not observing.
Key Requirements
- Real-world bachelor’s degree in Engineering or equivalent qualification
- Demonstrated mSc degree in Artificial Intelligence, Data Science, Engineering, or equivalent (near graduation acceptable)
- solving skills with the ability to synthesize complex information
- Communication Skills: Strong written and verbal communication skills, with the ability to convey technical concepts to non
- Project Management: Ability to handle multiple projects and deliverables effectively
- Comfort with team Teamwork: Demonstrated ability to work collaboratively in a multidisciplinary team environment
Job Description
What if you could shape a career as unique as you?
At WSP, you can always find opportunities to grow and do what matters to you. Make the most of our global reach to discover new challenges and chances to work with diverse, talented individuals who will help you expand your horizons.
WSP is hiring a Graduate in Artificial Intelligence (Emirati National) to support AI-driven initiatives across projects and internal processes. you’ll work with multidisciplinary teams to apply AI solutions, improve efficiency, and contribute to WSP’s digital transformation.
Audit – Assess how current processes are operating, identify areas for improvement, and propose initiatives aligned with your interests and areas of passion.
Research and Analysis – Conduct deep engineering research on the latest AI technologies and their applications in construction management.
Data Collection – Collect and analyse data from various sources to inform project decisions, AI integration strategies, and solve complex challenges.
ATS Resume Tips for This Role
To get past Applicant Tracking Systems (ATS) for this Graduate – Artificial Intelligence (Emirati National) opening, tailor your resume with the pointers below:
- Include these keywords verbatim in your Skills and Experience sections: Python, Deep Learning, TensorFlow, PyTorch, Machine Learning, NLP, LLM, Computer Vision, MLOps, Data Pipelines. ATS parsers match exact strings, not synonyms.
- Use a single-column layout. Two-column resumes break parsers — text gets scrambled or dropped.
- Save as .docx or standard .pdf (not scanned/image PDF). Avoid text boxes, headers, footers, graphics.
- Use standard section headings: Experience, Education, Skills, Certifications.
- Mirror the exact job title (Graduate – Artificial Intelligence (Emirati National)) in your target role line where truthful.
- Quantify results with numbers, percentages, currency. Metrics improve ATS scoring and human review.
- Spell acronyms out once (e.g., Search Engine Optimization (SEO)) so parser catches both forms.
- Font: Arial, Calibri, or Times New Roman at 10-12pt. Fancy fonts can render as unreadable glyphs.
Top 10 Interview Questions for This Role
- Walk me through your background and why you’re interested in this role.
- Describe a challenging project you owned end-to-end. What was the outcome?
- Tell me about a time you disagreed with a stakeholder. How did you handle it?
- How do you prioritize when everything on your plate feels urgent?
- How do you decide between fine-tuning a model vs. prompt engineering?
- Explain overfitting to a non-technical stakeholder.
- Walk through your data validation pipeline for training data.
- How do you evaluate model performance beyond accuracy?
- Describe your MLOps setup — from experimentation to production.
- How do you handle model drift once a system is in production?
How to Apply
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