73 AI Director jobs in Saudi Arabia

Job Description

• AI Model Development & Deployment: Lead design, development, and deployment of ML models, LLMs, and RAG systems with robust pipelines
• Technology Leadership: Monitor emerging AI technologies, conduct strategic assessments, and drive adoption of cutting-edge AI frameworks and methodologies
• Business Engagement: Collaborate with business units to identify AI use cases, translate requirements into technical solutions, and present strategic recommendations to executive leadership
• Team Leadership: Build, lead, and mentor teams of data scientists and ML engineers while fostering innovation and continuous learning
• AI Governance: Enforce AI governance frameworks, ethical guidelines, and organization-wide AI literacy initiatives
• Strategic Planning: Develop AI roadmaps, manage project budgets, and coordinate cross-functional initiatives to drive business transformation
• Innovation Management: Lead proof-of-concept initiatives, establish academic partnerships, and ensure scalable AI infrastructure for production applications

Job Requirements

• Education & Experience: Bachelor's degree in Computer Science/Data Science/ML or relevant fields (Master's preferred) with 7-10 years progressive AI/ML experience including 3-5 years in leadership roles
• Technical Expertise: Deep expertise in ML algorithms, LLMs, RAG architectures, and production deployment using frameworks and cloud services (GCP stack preferred)
• Programming & Data: Expert Python programming, strong SQL skills, experience with big data technologies (Spark, Kafka) and cloud AI platforms
• Leadership Experience: Proven track record building and scaling technical teams, managing P&L responsibility, and translating business requirements into AI solutions
• Business Acumen: Strong presentation skills to communicate complex technical concepts to stakeholders, experience with AI governance and regulatory compliance
• Industry Knowledge: Understanding of AI ethics, bias mitigation, responsible AI practices, and enterprise AI security best practices
• Preferred Qualifications: Cloud certifications, active conference and event participation and track record of successful AI product launches

Lucidya is an innovative SaaS company dedicated to transforming the world of customer experience and content analysis through the power of Machine Learning, Big Data, and now Generative AI technologies. Our platform helps organizations across the MENA region unlock actionable insights from unstructured data sources—social media, surveys, contact centers, and more—enabling them to understand their customers like never before.

As part of our mission, we are looking for a visionary VP of Engineering - AI to lead our engineering efforts in advancing our artificial intelligence capabilities and product offerings.

As the VP of Engineering - AI, you will shape Lucidya’s technical vision and drive execution across customer-facing AI features, AI infrastructure platforms, and cutting-edge research in GenAI and classical ML. Reporting directly to the CTO, you will lead multiple cross-functional engineering teams, scale AI innovations, and ensure that high-level company KPIs are met.

This is a high-impact leadership role that combines strategic direction, deep technical engagement, and organizational mentorship.

Key Responsibilities

• Define and drive the technical strategy for AI in alignment with Lucidya’s business and product objectives.
• Lead research and innovation in both classical machine learning and Generative AI (e.g., LLMs, RAG, fine-tuning).
• Translate cutting-edge AI research into scalable, production-grade features and platform capabilities.
• Build, scale, and mentor high-performing teams of engineers, data scientists, and AI researchers.
• Foster a culture of collaboration, accountability, and continuous improvement across engineering teams.
• Oversee the development, deployment, and integration of AI models within Lucidya’s SaaS products.
• Partner with Product and Platform Engineering teams to prioritize and deliver impactful AI-driven features.
• Ensure the scalability and reliability of AI infrastructure in collaboration with platform teams.
• Establish and enforce best practices across software development, MLOps, data governance, and responsible AI.
• Track and report on key technical and business KPIs to ensure AI initiatives deliver measurable value.
• Communicate technical progress, strategic direction, and key milestones to executive leadership.
• Manage team resources, hiring, and budgeting to meet project goals and organizational needs.
• Monitor industry trends and assess emerging AI technologies for adoption and differentiation.
• Champion internal R&D programs to explore and validate new AI methods and approaches.

Lucidya is an innovative SaaS company dedicated to transforming the world of customer experience and content analysis through the power of Machine Learning, Big Data, and now Generative AI technologies. Our platform helps organizations across the MENA region unlock actionable insights from unstructured data sources—social media, surveys, contact centers, and more—enabling them to understand their customers like never before.

As part of our mission, we are looking for a visionary VP of Engineering - AI to lead our engineering efforts in advancing our artificial intelligence capabilities and product offerings.

As the VP of Engineering - AI, you will shape Lucidya's technical vision and drive execution across customer-facing AI features, AI infrastructure platforms, and cutting-edge research in GenAI and classical ML. Reporting directly to the CTO, you will lead multiple cross-functional engineering teams, scale AI innovations, and ensure that high-level company KPIs are met.

This is a high-impact leadership role that combines strategic direction, deep technical engagement, and organizational mentorship.

Key Responsibilities

• Define and drive the technical strategy for AI in alignment with Lucidya's business and product objectives
• Lead research and innovation in both classical machine learning and Generative AI (e.g., LLMs, RAG, fine-tuning)
• Translate cutting-edge AI research into scalable, production-grade features and platform capabilities
• Build, scale, and mentor high-performing teams of engineers, data scientists, and AI researchers
• Foster a culture of collaboration, accountability, and continuous improvement across engineering teams
• Oversee the development, deployment, and integration of AI models within Lucidya's SaaS products
• Partner with Product and Platform Engineering teams to prioritize and deliver impactful AI-driven features
• Ensure the scalability and reliability of AI infrastructure in collaboration with platform teams
• Establish and enforce best practices across software development, MLOps, data governance, and responsible AI
• Track and report on key technical and business KPIs to ensure AI initiatives deliver measurable value
• Communicate technical progress, strategic direction, and key milestones to executive leadership
• Manage team resources, hiring, and budgeting to meet project goals and organizational needs
• Monitor industry trends and assess emerging AI technologies for adoption and differentiation
• Champion internal R&D programs to explore and validate new AI methods and approaches
  
  

• Bachelor's degree in Computer Science, Machine Learning, Data Science, or a related field is required. A Master's or PhD with a focus on AI is a strong plus
• 10+ years of experience in software engineering, including 5+ years in senior leadership roles focused on AI/ML
• Demonstrated success in delivering AI/ML products at scale, preferably within SaaS or enterprise environments
• Hands-on expertise in both classical machine learning and Generative AI (e.g., LLMs, RAG)
• Strong programming skills in languages such as Python, Java, or R, with proficiency in ML frameworks like TensorFlow, PyTorch, and Scikit-learn
• In-depth understanding of the ML/AI lifecycle, including pipelines, model training, evaluation, and deployment
• Proven ability to manage agile, cross-functional teams with a strong operational and delivery mindset
• Strategic thinking with a track record of aligning technical initiatives to business goals
• Excellent communication and storytelling skills, capable of bridging technical and non-technical audiences
• Passionate about mentoring, coaching, and growing engineering and data science talent
• Familiarity with modern cloud platforms, data infrastructure, MLOps and DevOps practices relevant to AI.

• Seniority level Executive

• Employment type Full-time

• Industries IT Services and IT Consulting

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Digital and AI Senior

Work Location: Saudi Arabia

About the Opportunity:

Are you open to an exciting opportunity with a prestigious, large-scale organisation where you would report directly to the Chief Information Officer? They are seeking a seasoned Digital & AI leader with proven expertise in artificial intelligence, machine learning, and robotic process automation (RPA), and a strong track record of driving successful digital transformation initiatives.

Requirements:

• Candidates who are based / or who have experience working in China, Malaysia, or Singapore are preferred
• 8+ years of experience in holding companies or different sectors

Key Responsibilities:

Emerging Technology Deployment and Adoption:

• Drive the implementation and scaling of Generative AI tools (e.g., Google Gemini) and Robotic Process Automation (RPA) solutions (e.g., UiPath) to enhance operational efficiency.
• Identify and prioritize high-impact use cases for emerging technologies across functions such as Finance, Supply Chain, Commercial, and HR.
• Promote organization-wide adoption through training, advocacy, and integration into business processes.
• Monitor the performance of deployed technologies, ensuring they deliver measurable value and scalability.

Innovation Program Leadership:

• Lead end-to-end innovation initiatives, from ideation to proof of concept (POC), proof of value (POV), and full-scale implementation.
• Collaborate with cross-functional stakeholders to identify opportunities where AI and emerging technologies can drive business value.
• Foster a culture of experimentation, learning, and continuous improvement.

Digital Integration with Ecosystem Partners:

• Strengthen the company's digital integration with suppliers and customers across all operational cycles, including Sales, Purchasing, Inventory, and Shipments.
• Enable seamless data exchange and collaboration through innovative digital solutions.
• Lead initiatives to enhance supply chain visibility and customer satisfaction.

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Machine Learning & AI Specialist

Location:
Dammam / Remote

Type:
Full-time

Objective:

Develop AI and computer vision solutions for fast and accurate item recognition and counting.

Responsibilities:

• Build and deploy computer vision models for SKU recognition in varied real-world settings.
• Implement 3D perception / Spatial Vision using
  LiDAR
  and other sensors for accurate mapping of items and shelves.
• Optimize models for on-device processing (mobile/tablet) to reduce latency.
• Integrate AI outputs with backend or ERP systems for real-time inventory updates.
• Preprocess, label, and manage datasets for training and testing models.
• Continuously monitor and improve model accuracy and performance.

Required Skills & Tools:

• Deep learning & computer vision (CNNs, 3D CNNs, object detection)
• Frameworks:
  TensorFlow, PyTorch, OpenCV
• On-device inference:
  TensorFlow Lite, ONNX, CoreML
• 3D sensing / LiDAR integration
• Data preprocessing, labeling, and model evaluation

Preferred:

• Augmented Reality (AR) for overlay information
• Self-supervised or semi-supervised learning techniques

About the role

We are seeking a talented Machine Learning Engineer to join our growing team. As a Machine Learning Engineer, you will play a pivotal role in optimizing ML models for efficient training and inference, deploying deep learning models in specialized hardware for inference usage, monitoring the performance and latency of deployed models, and maintaining ML infrastructure.

• Designing, building, supporting, and scaling our cloud and / or our on-premise ML infrastructure.
• Deploying deep learning models in production environments and optimizing their performance for inference on either GPU or CPU.
• Maintaining our infrastructure (on-prem and cloud) and preparing it for training and inference purposes.
• Monitoring deployed ML models for their performance, latency, and throughput using automated tools for monitoring and reporting.
• Evaluating and improving data science processes, identifying opportunities for automation, efficiency, and scalability.
• Collaborating with other teams, including product managers, data scientists, software engineers, data annotators, and business stakeholders, to ensure successful deployments of ML models.
• Staying up to date with the latest trends and advancements in ML engineering, ML models, and applying this knowledge to enhance the team's capabilities.
• Exploring and learning new technologies that can complement or replace our current stack to improve it.

• You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
• You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
• The fundamentals will be taken care of : competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best.
• You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
• We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.

Apply now

• Bachelor's or Master's degree in Computer Science or a related field.
• 2 years of experience in a similar role.
• Proficiency in Arabic language (Native Arabic speaker) is a must.
• Proficiency in one or more programming languages (e.g., Python, C, C++) with the ability to learn new languages.
• Experience with relational databases, including SQL queries, database definition, and schema design.
• Experience with deploying Deep learning frameworks (e.g. Tensorflow, Pytorch, Onnx) in production environments using inference frameworks (e.g. Nvidia Triton, TFXServing, TorchServe).
• Uphold best practices and principles around clean code, version control, testing, continuous integration and continuous deployment.
• Effective communication skills to convey technical solutions to end-users.
• Experience with monitoring ML models and reporting tools (e.g. grafana, and / or promethues).
• Experience with containerization technologies (e.g. Docker) is highly preferred.
• Experience with distributed computing systems is a plus.
• Experience with cloud platforms (e.g. AWS, GCP, OCI) is a plus.
• Knowledge of big data platforms like kafka, hadoop, and spark is a plus.

1. Build and maintain high-performance microservices using Kotlin and Spring Boot
2. Model relational schemas, optimize SQL queries, and manage data consistency across MySQL and PostgreSQL
3. Collaborate with data scientists to consume ML models (e.g., via REST, gRPC), embed intelligent decisioning into backend services
4. Develop and maintain RESTful APIs; define contracts for frontend, partner services, or AI inference layers
5. Contribute to Docker/Kubernetes-based deployments, CI/CD pipelines, and monitoring (Grafana, Prometheus, etc.)
6. Review code, guide peers on best practices, and participate in architectural discussions and roadmap planning

Skills

• 5+ years of experience building production-ready backend systems
• Expert-level knowledge of Kotlin and Spring Boot ecosystem
• Strong experience with microservices, API design, and distributed systems
• Hands-on experience with MySQL and PostgreSQL including schema design and query optimization
• Solid understanding of software design patterns, RESTful principles, and secure coding practices
• Experience with containerized environments and orchestrators (Docker, Kubernetes)
• Familiarity with integrating AI/ML models (e.g., Python-based APIs, TensorFlow/ONNX serving, or model inference endpoints)
• Strong communication skills and ability to work across engineering and data teams

Roles & Responsibilities:

• Design and implement machine learning models, algorithms, and deep learning applications and systems.
• Optimize and scale ML models for production.
• Collaborate with data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications.
• Monitor model performance and identify differences in data distribution that could potentially affect model performance in real-world applications.
• Ensure algorithms generate accurate user recommendations.
• Prepare and clean data for model training, including data wrangling, feature engineering, and handling missing values.
• Integrate machine learning models into production systems (web applications, APIs) using software engineering best practices.
• Document the machine learning development process and model performance for future reference and collaboration.
• Stay up to date with developments in the machine learning industry.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (preferred).
• At least 5 years of hands-on experience as machine learning engineer or similar role.
• Familiarity with Python, Java, C++, and R.

• Machine Learning Algorithms and Techniques (supervised, unsupervised, reinforcement learning).
• Software Engineering Principles (version control, testing, DevOps).
• Cloud Computing Platforms (AWS, Azure, GCP) (often a plus).
• Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms.
• In-depth knowledge of machine learning frameworks, like Keras or PyTorch.
• Familiarity with data structures, data modeling, and software architecture.
• Excellent time management and organizational skills.

Bachelor’s Degree in Computer Science or related field.

Computer Science fundamentals in object-oriented design, data structures, algorithms and complexity analysis.

• Proficiency in Python.
• Information Retrieval.
• Data Mining.
• Natural language Programming.
• Machine Learning
• Python Data Science stack (NLTK, Pandas, Numpy).
• Proficiency in HTML, Javascript, CSS and general Web 2.0 techniques.
• Experience taking a leading role in building complex software systems that have been successfully delivered to customers.
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.

Interested applicants should send their CVs with mentioning “machine learning specialist” in the subject line.