50 AI Ml jobs in Saudi Arabia

We're Hiring: Senior Technical Project Manager – Emerging Technologies (AI / IoT / ML)

Location:
Riyadh, Saudi Arabia

Experience:
10–14 Years (with 6+ years in Technical Project Management)

We are looking for a dynamic leader with a strong development background in
AI, IoT, Data Science, and Machine Learning
to drive complex, high-impact projects.

What You'll Do

• Lead end-to-end delivery of projects in AI, IoT, ML, and Data Science.
• Collaborate with cross-functional teams for seamless execution.
• Apply Agile, Scrum, and Kanban methodologies effectively.
• Drive enterprise-level integrations across systems and platforms.
• Communicate and align with stakeholders at both technical and executive levels.

What We're Looking For

• Bachelor's degree in Engineering or a related field.
• Strong hands-on development background in emerging technologies.
• 10–14 years of professional experience (6+ years in Technical Project Management).
• Expertise in Agile methodologies and enterprise development lifecycles.
• Excellent leadership, communication (Arabic & English), and stakeholder management skills.

We are particularly keen on candidates currently based in
Saudi Arabia, Jordan, Morocco, or Egypt
, open to relocating to Riyadh.

If this sounds like your next big opportunity, share your CV with us at

.

Required Qualifications

• 6+ years of experience in AIOps, SRE, or infrastructure engineering, including at least 2+ years working on AI/ML/GenAI workloads.
• Proven experience building and deploying GenAI or LLM-based solutions at scale.
• Deep expertise in container orchestration (Kubernetes, KubeRay), GPU provisioning, and cloud-native infrastructure.
• Strong programming skills in Python or Go, and experience working with ML workflows.
• Experience deploying open-source LLMs (e.g., LLaMA, Qwen) or custom fine-tuned models.
• Knowledge of vector databases (e.g., milvus, qdrant, Pinecone) in RAG pipelines.

Responsibilities

• Design and deploy GenAI workloads at scale, including LLMs and multimodal models using container orchestration platforms like Kubernetes, Ray, or KServe.
• Own the development of the AIOps pipeline, including data ingestion, feature engineering, model training, validation, deployment, and monitoring.
• Demonstrated experience with LLMOps, including prompt management, routing, guardrails, and logic fallback mechanisms.
• Size and allocate GPU/TPU resources for use cases such as RAG, chatbots, image/video generation, and LLM fine-tuning or inference.
• Collaborate with research teams to automate LLM pipelines from training to deployment using MLflow, and manage large-scale training jobs using schedulers like Kubeflow or SLURM.
• Engineer highly available and scalable infrastructure across cloud and hybrid platforms (AWS, GCP, Azure).

Good to Have

• Experience with LLM pretraining and fine-tuning.

Not just a job, but a career
Yokogawa, award winner for 'Best Asset Monitoring Technology' and 'Best Digital Twin Technology' at the HP Awards, is a leading provider of industrial automation, test and measurement, information systems and industrial services in several industries.

Our aim is to shape a better future for our planet through supporting the energy transition, (bio)technology, artificial intelligence, industrial cybersecurity, etc. We are committed to the United Nations sustainable development goals by utilizing our ability to measure and connect.

About The Team
Our 18,000 employees work in over 60 countries with one corporate mission, to "co-innovate tomorrow". We are looking for dynamic colleagues who share our passion for technology and care for our planet. In return, we offer you great career opportunities to grow yourself in a truly global culture where respect, value creation, collaboration, integrity, and gratitude are highly valued and exhibited in everything we do.

Job Purpose
We are seeking a highly skilled and motivated
AI Solutions Engineer
to join our team driving digital transformation in the
Oil & Gas and Petrochemicals
industries. In this role, you will be responsible for designing, developing, and deploying AI and machine learning solutions that optimize operations across upstream, midstream, and downstream segments. This position serves as a bridge between data science and industrial process engineering, delivering impactful solutions to real-world challenges.

The
AI/ML Digital Solution Architect
will be responsible for architecting AI/ML solutions and supporting analytical implementations for production operations in Oil & Gas, Petrochemicals, and other related domains. This individual will also own the business outcomes and implementation strategy of AI/ML initiatives, while supporting the Digital Enterprise Business Unit and Solution Division in establishing a competitive differentiation in the high-growth Middle East region.

Key Responsibilities & Accountabilities

• Conduct high-level technical analysis of customer challenges in the Oil & Gas and Petrochemical industries, leveraging AI/ML technologies. This includes gathering requirements, performing gap analyses, and exploring AI/ML applications to address customer needs.
• Identify business cases, support implementation, and ensure successful scaling of targeted AI applications within the assigned industry or domain.
• Engage with customers in designated technical areas to co-develop solutions that address process challenges and support business growth through AI and, where applicable, APC/RTO technologies.
• Collaborate with domain experts to identify opportunities for AI-driven process optimization, predictive maintenance, and operational efficiency improvements.
• Develop and validate machine learning models using time-series, sensor, and operational data (e.g., SCADA, DCS, PI System).
• Define solution architectures and develop detailed design specifications.
• Proactively engage with customers to define the overall technical approach for AI implementations.
• Demonstrate the ability to effectively collaborate with sales teams and contribute to securing customer orders.

Required Qualification And Experience

• Bachelor's degree in Process or Chemical Engineering and a minimum of 15 years of industry experience in AI-based solution development, engineering disciplines, and technical sales.
• At least 7 years of hands-on experience in designing or implementing APC or AI/ML applications within the Oil & Gas or Petrochemical industries. Experience with AI for control systems is a plus.
• Strong analytical and problem-solving skills, with a focus on developing practical and scalable solutions.
• In-depth knowledge of the Oil & Gas, Petrochemicals, or specialized chemical domains is essential.
• Willingness and ability to travel internationally across regions as required.
• Excellent communication skills in English, both written and verbal.
• Demonstrated resilience and persistence in driving projects to completion involving multiple stakeholders.
• Awareness of current trends and developments in the AI market.

Skills

• Strong hands-on experience with AI and Machine Learning technologies, including automated data collection, historian systems (OSI PI is a plus), data visualization, manufacturing quality and efficiency, SCADA systems, automated decision-making, workflow automation, database applications, and scheduling tools.
• Proficient in Python programming languages, with fluency in implementing solutions.
• Understanding of basic machine learning concepts (Supervised, Unsupervised learning, Reinforcement Learning, Large Language Model) and ability to use concrete algorithms (Linear Regression, K-Means, Support Vector Machine, XGBoost, etc) to implement solution in Python.
• Ability to use Cloud-based Machine Learning platform (e.g., Azure ML Studio, AWS SageMaker) is a plus.
• Ability to anticipate organizational needs for change and actively support company-wide programs, strategies, and initiatives.
• Capable of identifying and developing industry- or application-specific digital technologies suitable for business use.
• Skilled in creating environments that foster successful customer interactions and high satisfaction.
• Proactive in early engagement with customers to explore and establish long-term partnership opportunities.
• Strong persuasive and influencing skills, with the ability to guide customers toward solution adoption and drive project closure.
• Proven ability to build trust and credibility with stakeholders, facilitating alignment and decision-making across complex engagements.
• Experience with physical process simulators such as OmegaLand or Petro-SIM is preferred.

Yokogawa is an Equal Opportunity Employer. Yokogawa wants a diverse, equitable and inclusive culture. We will actively recruit, develop, and promote people from a variety of backgrounds who differ in terms of experience, knowledge, thinking styles, perspective, cultural background, and socioeconomic status. We will not discriminate based on race, skin color, age, sex, gender identity and expression, sexual orientation, religion, belief, political opinion, nationality, ethnicity, place of origin, disability, family relations or any other circumstances. Yokogawa values differences and enables everyone to belong, contribute, succeed, and demonstrate their full potential.

Are you being referred to one of our roles? If so, ask your connection at Yokogawa

about our Employee Referral process

Company Description

is a Saudi-based company at the forefront of the healthcare technology sector, specializing in advanced artificial intelligence. Our mission is to revolutionize healthcare by transforming standard Hospital Information Systems (HIS) and Electronic Health Records (EHR) into dynamic, intelligent systems. We provide real-time, evidence-based clinical support to align with the healthcare goals of Saudi Arabia's Vision 2030, enhancing patient outcomes and supporting medical professionals.

Role Description

This is a full-time online role for a Data Science Specialist located in Jeddah. The Data Science Specialist will be responsible for analyzing large datasets, developing statistical models, conducting data analysis, and utilizing data science techniques to extract insights. Day-to-day tasks include data analytics, developing data-driven solutions to improve patient outcomes, and collaborating with cross-functional teams to implement AI-driven healthcare solutions.

Qualifications

• Analytical Skills and Data Analysis skills
• Expertise in Data Science and Data Analytics
• Strong Statistics knowledge
• Proficient in programming languages such as Python or R
• Experience with machine learning algorithms and data visualization tools
• Excellent problem-solving and communication skills
• Ability to work collaboratively in a team environment
• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or related field
• Experience in the healthcare industry is a plus

About Mozn
Mozn is a rapidly growing technology firm revolutionising the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia and it's working to realise Vision 2030 with a proven track record of excellence in supporting and growing the tech ecosystem in Saudi Arabia and the GCC region. Mozn is the trusted AI technology partner for some of the largest government organisations, as well as many large corporations and startups.

We are in an exciting stage of scaling the company to provide AI-powered products and solutions both locally and globally that ensure the growth and prosperity of our digital humanity. It is an exciting time to work in the field of AI to create a long-lasting impact.

About The Role
We are seeking a
*Data Science Manager *
to join our team. In this leadership role, you will be responsible for guiding and developing a team of data scientists, driving the full lifecycle of model development, and ensuring delivery of high-quality, client-focused solutions across a range of business domains. You'll work closely with internal teams and external clients, leading initiatives that encompass a broad spectrum of data science applications.

What You'll Do

• Lead and mentor a team of data scientists, overseeing all aspects of model development, evaluation, and deployment.
• Own the data science project lifecycle—from ideation and experimentation to prototyping, productionization, and monitoring—ensuring delivery of impactful client solutions.
• Collaborate with engineering, product teams, and clients to understand requirements, translate business problems into data-driven solutions, and communicate results.
• Contribute to the design and improvement of data and software platforms, emphasizing scalable, reusable, and service-oriented solutions.
• Keep the team up to date with emerging technologies and industry trends in data science, machine learning, and AI, supporting continuous learning and innovation.
• Support business development efforts by engaging in client discussions, understanding client needs, and proposing data science solutions tailored to diverse domains.
• Foster an inclusive, collaborative, and high-performance team culture, focused on excellence and client satisfaction.
• Attract, develop, and retain top data science talent.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• 6+ years of relevant experience, with at least 4 years in data science leadership or management roles.
• Proven experience developing and deploying data science solutions in production environments.
• Broad knowledge of machine learning, statistical modeling, and data analysis.
• Proficiency in Python and experience with frameworks such as PyTorch or TensorFlow.
• Experience working with large, real-world datasets (structured and unstructured).
• Familiarity with scalable ML infrastructure, cloud computing, and distributed computing is a plus.
• Strong client-facing communication skills; ability to translate technical concepts for business stakeholders.
• Proficiency in Arabic is preferred.
• Demonstrated ownership, collaboration, and commitment to excellence.

Benefits
*Why Mozn? *

• 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.

Mozn is a rapidly growing technology firm revolutionising the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia and it’s working to realise Vision 2030 with a proven track record of excellence in supporting and growing the tech ecosystem in Saudi Arabia and the GCC region. Mozn is the trusted AI technology partner for some of the largest government organisations, as well as many large corporations and startups.

We are in an exciting stage of scaling the company to provide AI-powered products and solutions both locally and globally that ensure the growth and prosperity of our digital humanity. It is an exciting time to work in the field of AI to create a long-lasting impact.

About the role

We are seeking a Data Science Manager to join our team. In this leadership role, you will be responsible for guiding and developing a team of data scientists, driving the full lifecycle of model development, and ensuring delivery of high-quality, client-focused solutions across a range of business domains. You’ll work closely with internal teams and external clients, leading initiatives that encompass a broad spectrum of data science applications.

What you'll do

• Lead and mentor a team of data scientists, overseeing all aspects of model development, evaluation, and deployment.
• Own the data science project lifecycle—from ideation and experimentation to prototyping, productionization, and monitoring—ensuring delivery of impactful client solutions.
• Collaborate with engineering, product teams, and clients to understand requirements, translate business problems into data-driven solutions, and communicate results.
• Contribute to the design and improvement of data and software platforms, emphasizing scalable, reusable, and service-oriented solutions.
• Keep the team up to date with emerging technologies and industry trends in data science, machine learning, and AI, supporting continuous learning and innovation.
• Support business development efforts by engaging in client discussions, understanding client needs, and proposing data science solutions tailored to diverse domains.
• Foster an inclusive, collaborative, and high-performance team culture, focused on excellence and client satisfaction.
• Attract, develop, and retain top data science talent.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
• 6+ years of relevant experience, with at least 4 years in data science leadership or management roles.
• Proven experience developing and deploying data science solutions in production environments.
• Broad knowledge of machine learning, statistical modeling, and data analysis.
• Proficiency in Python and experience with frameworks such as PyTorch or TensorFlow.
• Experience working with large, real-world datasets (structured and unstructured).
• Familiarity with scalable ML infrastructure, cloud computing, and distributed computing is a plus.
• Strong client-facing communication skills; ability to translate technical concepts for business stakeholders.
• Proficiency in Arabic is preferred.
• Demonstrated ownership, collaboration, and commitment to excellence.
• 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.

Who Are We

HALA is a leading fintech player in the MENAP region that aims to redefine financial services and build the future bank of SMEs. HALA aims at empowering SMEs to start, run, and grow their businesses by providing them with cutting-edge financial and technological tools.

HALA currently holds multiple entities in UAE, Saudi Arabia and Egypt (including HALA Payments, HALA Cashier and HALA Logistics) and offers solutions that enable merchants to digitize their payments as well as manage their sales and operations.

Founded in 2017, HALA is currently duly licensed by the Saudi Arabian Central Bank as well as the Financials Services Regulatory Authority (FSRA) in Abu Dhabi Global Market.

About the Role

We're hiring a Data Scientist with 1-2 years of experience to help shape the future of AI and ML at HALA. You'll be working closely with leadership to define the roadmap, uncover high-impact use cases, and develop models that drive real business value.

This role is ideal for someone who enjoys the challenge of building from the ground up—bringing structure, experimentation, and vision to a space full of potential.

What You'll Do

• Support and Contribute to the ML Roadmap
  : Identify and prioritize AI/ML opportunities across key areas such as credit risk, fraud detection, customer acquisition, and churn prevention
• Prototype & Scale
  : Propose, design, build, and deploy ML models that brings value to HALA, starting with rapid prototyping and scaling up based on impact
• Cross-Functional Collaboration
  : Work hand-in-hand with teams across the company to deeply understand their challenges and co-create solutions that leverage data

What You Bring

• Strong Python and SQL skills, and experience with ML libraries like scikit-learn, XGBoost, LightGBM, or similar
• A strategic mindset: you're comfortable identifying business opportunities, prioritizing impact, and navigating ambiguity
• Clear communication and storytelling skills. You can turn data into action and rally teams around your ideas
• Experience (or interest) in working on use cases like credit scoring, fraud detection, or customer lifecycle modeling is a big plus
• Willingness to keep an open mind and learn on the job

Why Join Us?

You'll be joining a leading FinTech that's growing quickly—and we believe data will play a critical role in that growth. As an early member of the data science team, you'll have the autonomy to explore, the support to execute, and the opportunity to shape how machine learning creates value across the organization.

What We Offer You
We believe you will love working at HALA

• We have an inclusive and diverse culture that encourages innovation and flexibility in remote, in-office, and hybrid work setups.
• We offer highly competitive compensation packages, including the potential for shares.
• We prioritize personal development and offer regular training and an annual learning stipend to tackle new challenges and grow your career in a hyper-growth environment.
• Join a talented team of over 30 nationalities working in 7 countries and gain valuable experience in an exciting industry.
• We offer autonomy, mentoring, and challenging goals that create incredible opportunities for both you and the company.
• 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.

If you think you have what it takes to join a remarkable team #apply_now

Role Purpose

To lead a team of data scientists within the Analytics Department in order to develop advanced machine learning models, deliver actionable insights through corporate reporting, and oversee the creation of predictive models, advanced analytics, and data visualizations within the set KPIs, agreed budgets, and adopted policies and procedures.

Responsibilities for Internal Candidates

Key Accountability Areas

Key Activities

Operational Management

• Lead, mentor, and develop a team of data scientists
• Actively participate in on-the-job training, mentoring and coaching of subordinates
• Provide clear direction, prioritize tasks, assign and delegate responsibility and monitor the workflow
• Promote a high-performance working environment embracing SANS's values
• Conduct regular performance reviews and provide coaching to team members
• Identify skill gaps and organize training programs to enhance team capabilities
• Provide recurring productivity reports on department progress and projects pipeline.
• Recruit, onboard, and retain top talent for the data science section

Budget Management

• Develop and manage budget and supporting business cases for the data science and reporting section including ML operations infrastructure.
• Justify budget requests to senior leadership by demonstrating the ROI of data science and analytics initiatives.
• Develop and negotiate contracts with tooling, infrastructure and service providers to optimize costs and service quality

Stakeholder and C-Suite Communication

• Generate and present regular operational and corporate performance insights and reports to senior leadership.
• Translate complex technical findings into actionable insights and strategic recommendations for non-technical audiences.
• Facilitate collaboration with IT and engineering stakeholders to ensure data science infrastructure needs are realized
• Build strong relationships with cross-functional teams to ensure alignment and collaboration on data-driven initiatives.
• Educate stakeholders on data science best practices.

Data science and ML products management

• Conducting discovery meetings to collect, analyze, clarify and document business requirements for data science and corporate reporting.
• Establish and monitor value metrics encompassing the full cycle of envisaged and developed data science products
• Continuously identify opportunities for data science products where value can be added to the business domain.
• Ensure that machine learning models and analytics solutions are scalable, reliable, and aligned with business needs.
• Manage advanced analytics workload including A/B and multivariate experiments, design and implement exploratory analysis and insight generation, all in close collaboration with partners across the Data management directorate and business groups.
• Collaborate with engineering and IT teams to integrate data science products into existing systems and workflows.
• Oversee the analysis of corporate and operational workstreams to provide periodic descriptive reporting and on-demand Diagnosis on key observed patterns for decision making purposes.
• lead the development efforts for provision of descriptive, predictive and diagnostic analysis for relevant constituencies.
• Develop strategy and roadmap for data science products while ensuring that defined path is consistent with the enterprise vision.
• Lead iterative data science products development process from idealization, through the implementation stage and all the way to the launch.
• Develop plans for ML models features/services delivery defining business goals, timelines, and roadmaps.
• Partner with business functions leads to proactively explore and overcome business problems through quantitative analytics levering established data science solutions.
• Support corporate planning and strategy functions in researching and analyzing industry operational and data related trends and developing market diligence periodically through quantitative reports and aggregation of relevant data from premium online/offline sources.
• Oversee the team's execution of key technical activities including: Data exploration and pre-processing, statistical analysis and modeling, features engineering, models evaluation, data visualization and communication, and collaborative problem solving

Engineering management

• Participate in planning and executing workload related to deploying and expanding ML models hosting platforms at the back-end and front-end service layers
• Lead the deployment and configuration of developed data science solutions.
• Oversee the ML models development workload cadence includes establishment of and sustenance of devOPS and CICD practices and cadence, while ensuring engineering standards, including version control, code reviews, and testing protocols are maintained
• Develop, manage, and maintain engineering plans related to data science workload; work closely with enterprise and operations engineering teams.
• Implement agile methodologies and project management frameworks to streamline team operations and improve delivery timelines.
• Manage technical debt by prioritizing refactoring, documentation, and process improvements.

Policies, Processes and Procedures

• Support in monitoring day-to-day activities to ensure compliance with stipulated policies and procedures
• Contribute to the identification of opportunities for continuous improvement of systems and processes taking into account leading practices, changes in business environment, cost reduction and productivity improvement

People Management

• Actively participate in on-the-job training, mentoring and coaching of subordinates
• Provide clear direction, prioritize tasks, assign and delegate responsibility and monitor the workflow
• Promote a high-performance working environment embracing SANS's values

Qualifications for Internal Candidates

Knowledge and Experience

• Minimum 6 years of experience in Data Science & Reporting, preferably leading and managing teams of data scientists and data analysts and budget management, resource allocation, and vendor negotiations.

Desirable:

• Referenced hands-on experience: team lead or unit manager/supervisor managing the operations and services of a data science team in a technology or engineering organization.
• Math / Quantitative skills: Skills with creating simulations, Erlangs theory for capacity planning, Hypothesis testing, Linear Regression, Logistic Regression, Outliers Detection, Linear Algebra with knowledge of Matrices attributes, knowledge and application of GLM (Generalized Linear Model)
• Strong scripting skills (e.g., Python, Bash) and knowledge of coding for creating automation scripts and integrating tools , and SQL/SPARK, JAVA/SCALA, Hadoop stack, C/C + for scripting/development on distributed/unstructured systems, and big data technologies such as Spark for handling and processing large datasets , and Python or PyTorch, Tensorflow, KERAS, Scikit-learn, XGBoost or similar stack for data manipulation, analysis, and data science modelling implementation.
• Familiarity or Ability to work with task management tools (JIRA, Microsoft Azure DevOPS boards), and Microsoft power platform , and hands on experience with popular SaaS services for database, developer and analytics (GCP, AWS or Azure)

Education and Certifications

• Bachelor's Degree in Computer Engineering, Data Science, Computer science, Cybersecurity, Statistics, Engineering or equivalent is required.

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