497 Machine Learning Manager jobs in Saudi Arabia

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.

Overview

Join to apply for the Machine Learning Engineer - Riyadh role at Mozn .

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 organizations, 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.

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 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.

• 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.

• 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.

• Seniority level: Entry level
• Employment type: Full-time
• Job function: Engineering and Information Technology
• Industries: Software Development

Riyadh, Riyadh, Saudi Arabia

As a Senior Machine Learning Engineer specializing, you will lead the development and implementation of machine learning algorithms and models to enhance our mapping and location-based services. You will be responsible for leveraging machine learning techniques to extract insights, automate processes, and improve the accuracy and relevance of our map data.

Key Responsibilities:

1. Algorithm Development: Lead the design, development, and optimization of machine learning algorithms and models for various mapping applications, including data analysis, feature extraction, image processing, and predictive modeling.
2. Data Processing and Analysis: Collaborate with data engineers to preprocess, clean, and analyze map data, including satellite imagery, LiDAR data, and point cloud data, to extract relevant features and patterns.
3. Model Training and Evaluation: Train, validate, and evaluate machine learning models using large-scale datasets to achieve high accuracy, robustness, and scalability for mapping applications, such as road detection, object recognition, and semantic segmentation.
4. Integration and Deployment: Integrate machine learning models into existing mapping systems and workflows, ensuring seamless deployment and interoperability with other software components. Collaborate with software engineers to develop APIs and interfaces for model integration.
5. Performance Optimization: Optimize machine learning algorithms and models for performance, efficiency, and scalability, including algorithm parallelization, hardware acceleration, and deployment on cloud platforms.
6. Research and Innovation: Stay updated on the latest advancements in machine learning, computer vision, and geospatial technologies, and apply innovative techniques to solve mapping-related challenges and drive continuous improvement.

Qualifications:

• Master's or Ph.D. degree in computer science, machine learning, artificial intelligence, or a related field.
• 5 years of experience in machine learning research and development, with a focus on computer vision, geospatial analysis, or mapping applications.
• Proficiency in machine learning frameworks and libraries, such as TensorFlow, PyTorch, and OpenCV.
• Strong programming skills in Python, C++, or another relevant language, with experience in software development and version control systems.
• Experience with geospatial data processing and analysis tools, such as GDAL, PostGIS, and QGIS.
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
• Effective communication and leadership skills, with experience mentoring junior team members and collaborating with cross-functional teams.

Overview

Staff Machine Learning Engineer at Mozn. Mozn is a technology firm in Artificial Intelligence and Data Science, headquartered in Riyadh, Saudi Arabia, supporting and growing the tech ecosystem in Saudi Arabia and the GCC. Mozn partners with government organizations and large corporations and startups. We are scaling to provide AI-powered products and solutions locally and globally.

We are seeking a talented hands-on Staff Machine Learning Engineer to lead one of ML Engineering teams at OSOS. The ideal candidate is a native Arabic speaker with a strong foundation in AI and machine learning, and a track record of building and deploying real-world AI systems. You will play a pivotal role in optimizing ML models for training and inference, deploying deep learning models in specialized hardware for inference, monitoring performance and latency, maintaining inference pipelines, and sustaining ML infrastructure.

• Lead a multidisciplinary team of ML engineers focused on advanced Arabic language solutions and products
• Design, build, support, and scale cloud and/or on-premise ML infrastructure
• Deploy deep learning models in production and optimize performance for inference on GPU or CPU
• Maintain infrastructure for training and inference (on-prem and cloud)
• Monitor deployed ML models for performance, latency, and throughput using automated tools
• Evaluate and improve data science processes, identifying opportunities for automation, efficiency, and scalability
• Collaborate with product teams, data scientists, software engineers, data annotators, and stakeholders
• Guide the team on best practices in ML engineering, software design, testing, versioning, and deployment
• Stay up to date with ML trends and apply knowledge to enhance the team's capabilities
• Explore and learn new technologies to improve the current stack and enable modernization
• Ensure the team adopts modern ML tooling and infrastructure, including vector databases, orchestration tools, and scalable APIs

• Bachelor's or master's degree in computer science or a related field
• 8+ years of experience in a similar role
• Proficiency with MLOps tools, CI/CD for ML, and scalable backend architecture
• Proficiency in Arabic language (native) is a must
• Proficiency in one or more programming languages (e.g., Python, C, C++)
• Experience with relational databases, SQL, schema design
• Experience deploying deep learning frameworks (TensorFlow, PyTorch, ONNX) in production using inference frameworks (e.g., Nvidia Triton, TorchServe)
• Uphold best practices around clean code, version control, testing, CI/CD
• Effective communication to convey technical solutions
• Experience with monitoring ML models and reporting tools (e.g., Grafana, Prometheus)
• Experience with containerization (e.g., Docker) is highly preferred
• Experience with distributed systems is a plus
• Experience with cloud platforms (e.g., AWS, GCP, OCI) is a plus
• Knowledge of big data platforms (Kafka, Hadoop, Spark) is a plus
• Experience managing remote or distributed teams

• Competitive compensation and health insurance
• Enabling culture and opportunities to work with leading minds in AI
• Career growth in a high-growth organization at the forefront of AI in the Middle East

About the role

We are seeking a talented hands-on Staff Machine Learning Engineer to lead one of ML Engineering teams at OSOS. The ideal candidate is a native Arabic speaker with a strong foundation in AI and machine learning, a record of building and deploying real-world AI systems. As a Staff 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, responsible for inference and serving the pipelines, and maintaining ML infrastructure.

• Leading a multidisciplinary team of ML engineers working on advanced Arabic language solutions and products
• 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.
• Guide the team in using best practices in ML engineering, software design, testing, versioning, and deployment for AI products
• 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.
• Ensure the team adopts modern ML tooling and infrastructure, including vector databases, orchestration tools, and scalable APIs

• Bachelor's or master's degree in computer science or a related field
• +8 years of experience in a similar role
• Proficiency with MLOps tools, CI/CD pipelines for ML, and scalable backend architecture
• 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
• Experience managing remote or distributed teams
• 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

Overview

About nybl: We are developing an Ai ecosystem that enables businesses, in any industry, to deploy artificially intelligent solutions using both our platform and applications. Our technology allows anyone to build Ai solutions without writing a line of code or needing a degree in Data Science. Our ecosystem is world changing from healthcare to agriculture, education to industry, the applications of our technology are truly limitless.

We're on the hunt for an enthusiastic Junior Engineer to help with engineering calculations and machine learning algorithms for Electrical Submersible Pumps (ESPs). This position is perfect for someone who has a solid technical foundation in petroleum, electrical, or mechanical engineering, is keen on production optimization, and loves using data science and programming to tackle real-world issues in the energy field.

• Gather, organize, and examine ESP field data (production, electrical, and fluid characteristics).
• Help in creating and verifying ESP performance calculations (head, power, efficiency, pumpability ranges).
• Apply correlations for fluid characteristics and IPR/VLP models.
• Assist in designing and testing machine learning models for optimizing ESP and predicting failures.
• Create and update Python/Excel/MATLAB scripts for engineering and ML processes.
• Record algorithms, generate reports, and present results for engineering and management teams.
• Work with senior engineers to incorporate solutions into production monitoring systems.

• Bachelor’s degree in Petroleum Engineering.
• Fundamental understanding of ESP operation and production systems (academic experience or internships are acceptable).
• Proficiency in Python (preferred), MATLAB, or VBA for engineering tasks.
• Knowledge of data analysis, regression, and basic machine learning methods.
• Analytical approach with a focus on detail and a willingness to learn.

Overview

About nybl: We are developing an AI ecosystem that enables businesses in any industry to deploy AI solutions using our platform and applications. Our technology lets anyone build AI solutions without writing code or needing a degree in Data Science. Our ecosystem has potential across healthcare, agriculture, education, and industry with limitless applications.

We're on the hunt for an enthusiastic Junior Engineer to help with engineering calculations and machine learning algorithms for Electrical Submersible Pumps (ESPs). This position is ideal for someone with a solid technical foundation in petroleum, electrical, or mechanical engineering, an interest in production optimization, and a passion for using data science and programming to tackle real-world energy challenges.

• Gather, organize, and examine ESP field data (production, electrical, and fluid characteristics).
• Help in creating and verifying ESP performance calculations (head, power, efficiency, pumpability ranges).
• Apply correlations for fluid characteristics and IPR / VLP models.
• Assist in designing and testing machine learning models for optimizing ESP and predicting failures.
• Create and update Python / Excel / MATLAB scripts for engineering and ML processes.
• Record algorithms, generate reports, and present results for engineering and management teams.
• Work with senior engineers to incorporate solutions into production monitoring systems.

• Bachelor’s degree in Petroleum Engineering.
• Fundamental understanding of ESP operation and production systems (academic experience or internships are acceptable).
• Proficiency in Python (preferred), MATLAB, or VBA for engineering tasks.
• Knowledge of data analysis, regression, and basic machine learning methods.
• Analytical approach with a focus on detail and a willingness to learn.

About nybl:

We are developing an Ai ecosystem that enables businesses, in any industry, to be able to deploy artificially intelligent solutions using both our platform and applications. Our technology allows anyone to build Ai solutions without writing a line of code or needing a degree in Data Science. Our ecosystem is world changing from healthcare to agriculture, education to industry, the applications of our technology are truly limitless.

We're on the hunt for an enthusiastic Junior Engineer to help with engineering calculations and machine learning algorithms for Electrical Submersible Pumps (ESPs). This position is perfect for someone who has a solid technical foundation in petroleum, electrical, or mechanical engineering, is keen on production optimization, and loves using data science and programming to tackle real-world issues in the energy field.

• Gather, organize, and examine ESP field data (production, electrical, and fluid characteristics).
• Help in creating and verifying ESP performance calculations (head, power, efficiency, pumpability ranges).
• Apply correlations for fluid characteristics and IPR/VLP models.
• Assist in designing and testing machine learning models for optimizing ESP and predicting failures.
• Create and update Python/Excel/MATLAB scripts for engineering and ML processes.
• Record algorithms, generate reports, and present results for engineering and management teams.
• Work with senior engineers to incorporate solutions into production monitoring systems.

• Bachelor’s degree in Petroleum Engineering.
• Fundamental understanding of ESP operation and production systems (academic experience or internships are acceptable).
• Proficiency in Python (preferred), MATLAB, or VBA for engineering tasks.
• Knowledge of data analysis, regression, and basic machine learning methods.
• Analytical approach with a focus on detail and a willingness to learn.

Build the ML infrastructure powering Saudi Arabia's financial transformation.

We're Aajil (previously BuildNow), backed by leading regional VCs and operating at the heart of Saudi Arabia's $50B+ SME market. We've already revolutionized lending timelines from 3 months to hours. Now we're building what's next: real-time, intelligent credit decisions that will transform how millions of SMEs access capital.

As Machine Learning Lead, you'll architect the intelligence layer for the Kingdom's most ambitious fintech. With exclusive access to the data we have, you'll build ML systems that don't exist anywhere in the region — yet.

Saudi Arabia is experiencing the world's most ambitious economic transformation. Vision 2030 has created unprecedented opportunities for those bold enough to seize them. The government is digitizing at breakneck speed, regulations are evolving in real-time, and there's genuine will to make the Kingdom a global fintech hub.

This isn't another "emerging market" story. This is ground zero for building financial infrastructure that will define the next decade.

You'll lead our ML efforts from our Riyadh headquarters, building systems that process billions in BNPL decisions:

• Own the evolution from hours → minutes → real-time credit decisions
• Build and lead a world-class ML team, mixing top Saudi talent with international experts
• Architect production ML systems handling thousands of daily decisions with 99.9% uptime

Essential Experience:

• 8+ years building and deploying ML systems in production environments
• Proven track record leading ML teams and delivering business impact
• Deep expertise in credit risk, fraud detection, or financial ML systems
• Experience with real-time ML serving, feature stores, and MLOps at scale
• Strong engineering fundamentals and architectural thinking
• Track record of hiring and developing exceptional ML talent

The X-Factors:

• You've built ML systems that handle serious money and serious scale
• You've worked in high-growth environments where perfect is the enemy of shipped
• You're excited by exclusive data access and building unique competitive advantages
• You see the opportunity in Saudi Arabia while others see only challenges

Unprecedented Opportunity : The Kingdom is investing billions in digital transformation. Your work here will have 10x the impact of mature markets.

Exclusive Data Access : Through government partnerships, we have data advantages that otherstartups dream of. Tens of millions of transactions— this is your ML playground.

This role isn't for everyone. It's for ML leaders who see massive opportunity where others see risk. Who want to build something that matters, not optimize something that already works.

Send us:

1. Your GitHub/papers/portfolio — show us what you've built at scale
2. A brief note on why Saudi Arabia, why now, why Aajil — we want missionaries, not mercenaries

P.S. We've already automated credit assessments from the industry standard of 3 months to hours in one of the world's most complex markets. If you think that's just the beginning of what's possible, we should talk.

Location : Riyadh, Saudi Arabia (relocation support provided)

Start Date : Q3 2025