AI Engineer, Specialist

Master-Works is hiring an AI Engineer, Specialist in Riyadh, Saudi Arabia. Level rates it ; you can apply on Level.

Level's read on this job

Level rates this AI engineer role Builds AI ●●●●: the job is building AI systems.
The posting mentions PyTorch, TensorFlow and MLOps among its tools and skills.
Level classes it as a mid-level role.
Master-Works has 30 other open roles on Level.
This posting went up in the last few days.

AI in this role

pytorchtensorflow

ml-opscomputer-visionnlpspeech

Nabeh a subsidiary of Master Works, delivers AI-powered solutions that help organizations automate operations, boost efficiency, and drive innovation. Its expertise spans computer vision, LLM applications, speech-to-text, data intelligence, and low-code AI solutions.

Nabeh is looking for an AI Engineer, Specialist to develop, optimize, test, and deploy AI and machine learning solutions across Computer Vision, Natural Language Processing (NLP), Speech AI, and Generative AI.

Key Responsibilities

Design, develop, train, fine-tune, evaluate, and optimize machine learning and deep learning models.
Build AI solutions across Computer Vision, NLP, Large Language Models (LLMs), Speech-to-Text, and Text-to-Speech.
Prepare, process, and manage datasets for model training, validation, and evaluation.
Integrate AI models into enterprise applications and systems using REST APIs.
Support AI model deployment across cloud, on-premises, and edge environments.
Collaborate with AI, Backend, DevOps, and QA teams to move prototypes into production.
Monitor model performance, troubleshoot issues, and maintain technical documentation.

Requirements

Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
3–5 years of hands-on experience in AI/ML engineering and model development.
Strong proficiency in Python and experience with PyTorch or TensorFlow.
Knowledge of Computer Vision, NLP, LLMs, and Speech AI.
Experience with REST APIs, SQL, Pandas, and NumPy.
Familiarity with Git, Docker, and foundational MLOps practices.
Understanding of the AI/ML lifecycle, including model development, evaluation, deployment, and monitoring.
Strong analytical thinking, problem-solving, and troubleshooting skills.

How we rate this

AI Engineer, Specialist at Master-Works rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

AI Engineer, Specialist is an open job at Master-Works.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Riyadh, Riyadh Province, Saudi Arabia.
The job was posted on October 18, 2026.
Seniority: mid.
Applications are handled by Master-Works. Apply on Master-Works

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsComputer visionNLPSpeechPyTorchTensorFlow

Also common in AI engineer jobs at this level

AWS AI agents Azure RAG Google Cloud Java

Pay

Typical AI engineer job: $184k

This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
What have you built with speech recognition or text-to-speech, and where did it break?
Walk me through how you've used PyTorch in your day-to-day work.

Adapt your resume

List these exact terms on your resume: ML Ops, Computer vision, NLP, Speech, and PyTorch. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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