107 Machine Learning Engineer jobs in Saudi Arabia

• Riyadh, SA - Hybrid (Remote and In Person)

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:

• 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.
• 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.
• 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.
• 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.
• Performance Optimization: Optimize machine learning algorithms and models for performance, efficiency, and scalability, including algorithm parallelization, hardware acceleration, and deployment on cloud platforms.
• 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.

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.

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.

Get AI-powered advice on this job and more exclusive features.

At Wittify.ai, we are on a mission to build the most advanced Arabic conversational AI, and voice is at the heart of this mission. We are developing human-like, multilingual TTS systems that redefine naturalness, expressiveness, and adaptability for real-world business and consumer applications.

We are looking for aMachine Learning Engineer (Advanced Speech & TTS) to lead the development of next-generation TTS models and voice cloning systems that set new benchmarks in the industry.

Role Overview

As a Machine Learning Engineer (Advanced Speech & TTS), you will design, train, and optimize cutting-edge TTS models using diffusion-based architectures, neural vocoders, and voice cloning techniques. You will collaborate with our speech scientists and AI engineers to build production-ready models that deliver ultra-realistic, controllable, and deployable Arabic speech synthesis.

What You’ll Do

• Design, implement, and train state-of-the-art TTS models, including:
• Diffusion-based architectures for ultra-natural speech
• Non-autoregressive models for real-time performance
• Multi-speaker TTS and zero-shot voice cloning
• Develop and optimize high-fidelity neural vocoders to achieve studio-quality audio with low-latency streaming capabilities

Voice Cloning & Adaptation

• Build speaker adaptation and voice cloning pipelines enabling rapid cloning of new voices with minimal data (few-shot or zero-shot approaches)
• Implement flexible voice style transfer, emotion conditioning, and controllable prosody for human-like speech generation
• Create scalable pipelines for audio-text alignment, phoneme extraction, and dataset augmentation across multiple Arabic dialects
• Utilize forced alignment tools (MFA) and phoneme-based modeling to enhance synthesis accuracy
• Conduct rigorous objective and subjective evaluations, including MOS testing, speaker similarity scoring, and intelligibility assessments
• Benchmark models against industry-leading TTS systems to continuously improve performance

Deployment & Optimization

• Optimize models for production using ONNX, TensorRT, quantization, and pruning to achieve real-time inference on cloud and edge devices
• Stay updated with the latest TTS, voice cloning, and speech synthesis research (NeurIPS, ICASSP, Interspeech, arXiv) and integrate breakthroughs into production systems

Required Qualifications

Education & Experience

• Master’s or PhD in Machine Learning, Speech Processing, Signal Processing, or related fields
• 3+ years of hands-on experience building and deploying advanced neural TTS or voice cloning systems

Technical Expertise

• Deep proficiency in Python and PyTorch (preferred) or TensorFlow
• Proven experience with:
• Diffusion-based TTS models
• Multi-speaker TTS and voice cloning (speaker embedding, speaker adaptation, zero-shot cloning)
• Neural vocoders and deployment optimization for real-time performance
• Strong understanding of DSP fundamentals and neural audio modeling

Nice to Have

• Experience with multilingual or low-resource TTS adaptation, especially Arabic dialects
• Contributions to open-source TTS or speech synthesis projects
• Familiarity with LLM-integrated TTS approaches and context-aware speech synthesis

Why Join Us

• Lead the development of Arabic-first voice AI systems at the frontier of speech synthesis research
• Work in a collaborative environment with world-class AI engineers, linguists, and product teams
• Join a mission-driven startup shaping the future of human-computer voice interactions
• Enjoy flexible work arrangements, competitive compensation, and opportunities for rapid growth

Apply now and be part of building the future of Arabic voice AI.

Together, let’s wit-tify the future.

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Engineering and Information Technology
• Industries Technology, Information and Internet

Referrals increase your chances of interviewing at Wittify.ai by 2x

Get notified about new Machine Learning Engineer jobs in Riyadh, Riyadh, Saudi Arabia .

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

Aramco energizes the world economy.

Aramco occupies a unique position in the global energy industry. We are the world’s largest producer of hydrocarbons (oil and gas), with the lowest upstream carbon intensity of any major producer.

With our significant investment in technology and infrastructure, we strive to maximize the value of the energy we produce for the world along with a commitment to enhance Aramco’s value to society.

Headquartered in the Kingdom of Saudi Arabia, and with offices around the world, we combine market discipline with a generations’ spanning view of the future, born of our nine decades experience as responsible stewards of the Kingdom’s vast hydrocarbon resources. This responsibility has driven us to deliver significant societal and economic benefits to not just the Kingdom, but also to a vast number of communities, economies, and countries that rely on the vital and reliable energy that we supply.

We are one of the most profitable companies in the world, as well as amongst the top five global companies by market capitalization.

We are seeking an Artificial Intelligence Specialist (AIS) to join the Gas Operations Technical Support Division.

The Gas Operation Technical Support Division is responsible for providing Artificial Intelligence (AI)-powered solutions to all Gas Plants. The objective is to leverage AI technological advancements to support data-driven decisions in Safety, Environment, Energy, Efficiency, and value creation.

The primary role of the Artificial Intelligence Specialist is to work closely with the Gas Business Line and other corporate entities to manage AI business cases starting from challenges/opportunities identification, solution scouting, formulating, scoping, funding, PoC, deployment, evaluation, and value tracking.

The successful candidate will be required to perform the following:

• Lead a multidisciplinary team to oversee and monitor Gas AI business cases starting from challenges/opportunities identification, solution scouting, formulating, scoping, funding, PoC, deployment, evaluation, and value tracking.
• Collaborate with internal/external entities and with 3rd parties to drive AI implementation advancement in Gas.
• Prioritize AI business cases and oversee the quality of all deliverable packages required to secure funds.
• Develop a roadmap to scale up AI solutions across the Business Line.
• Facilitate and monitor AI solutions development and execution phases with all stakeholders.
• Develop Generative AI cases for Safety, Environment, Operations, and Maintenance.
• Apply statistical analysis methods to test hypotheses and validate results based on the project or use-case.
• Build and train machine learning models to solve specific problems and optimize models for performance and accuracy such as anomaly detection algorithms or predictive models.
• Assess, identify, and mitigate key risks associated with cybersecurity and ensure that data practices adhere to the company’s regulations and data privacy standards.
• Act as the Gas AI focal point of contact and coordinator with all other entities.

• The candidate must hold a Bachelor’s degree in Engineering, Computer Science, Data Science and Analytics, Machine Learning, or AI, or in a related field from an accredited university. An advanced degree in an engineering discipline with a focus on machine learning, artificial intelligence, applied statistics, or operations research is desirable.
• 10 years of experience in building data analytics-based products or machine learning models.
• Able to program in different languages such as Python and has experience with statistics and data cleaning libraries and methodologies, in addition to visualization tools such as Power BI or Tableau.
• Strong knowledge in regression and classification, association rules & clustering, big data, databases & SQL, textual analysis (NLP), neural networks, and advanced visualization. Understanding of statistical and predictive and optimization algorithms is required.
• Analytical and problem-solving skills to derive insights and opportunities from data.
• Basic project management skills to plan, execute, and deliver data science projects.
• Past experience in leading AI solution deployment projects for Oil and Gas is preferable.
• Knowledge of plant automation systems, standard real-time interfaces such as OPC, and process historians such as PI is desirable.

Working environment

Our high-performing employees are drawn by the challenging and rewarding professional, technical, and industrial opportunities we offer, and are remunerated accordingly.

At Aramco, our people work on truly world-scale projects, supported by investment in capital and technology that is second to none. And because, as a global energy company, we are faced with addressing some of the world’s biggest technical, logistical, and environmental challenges, we invest heavily in talent development.

We have a proud history of educating and training our workforce over many decades. Employees at all levels are encouraged to improve their sector-specific knowledge and competencies through our workforce development programs – one of the largest in the world.

Job ID: 15053

Tagged as: Gas Ventures Dept

Aramco energizes the world economy.

Aramco occupies a unique position in the global energy industry. We are the world's largest producer of hydrocarbons (oil and gas), with the lowest upstream carbon intensity of any major producer.

With our significant investment in technology and infrastructure, we strive to maximize the value of the energy we produce for the world along with a commitment to enhance Aramco's value to society.

Headquartered in the Kingdom of Saudi Arabia, and with offices around the world, we combine market discipline with a generations' spanning view of the future, born of our nine decades experience as responsible stewards of the Kingdom's vast hydrocarbon resources. This responsibility has driven us to deliver significant societal and economic benefits to not just the Kingdom, but also to a vast number of communities, economies, and countries that rely on the vital and reliable energy that we supply.

We are one of the most profitable companies in the world, as well as amongst the top five global companies by market capitalization.

We are seeking an Artificial Intelligence Specialist (AIS) to join the Gas Operations Technical Support Division.

The Gas Operation Technical Support Division is responsible for providing Artificial Intelligence (AI)-powered solutions to all Gas Plants. The objective is to leverage AI technological advancements to support data-driven decisions in Safety, Environment, Energy, Efficiency, and value creation.

The primary role of the Artificial Intelligence Specialist is to work closely with the Gas Business Line and other corporate entities to manage AI business cases starting from challenges/opportunities identification, solution scouting, formulating, scoping, funding, PoC, deployment, evaluation, and value tracking.

The successful candidate will be required to perform the following:

• Lead a multidisciplinary team to oversee and monitor Gas AI business cases starting from challenges/opportunities identification, solution scouting, formulating, scoping, funding, PoC, deployment, evaluation, and value tracking.
• Collaborate with internal/external entities and with 3rd parties to drive AI implementation advancement in Gas.
• Prioritize AI business cases and oversee the quality of all deliverable packages required to secure funds.
• Develop a roadmap to scale up AI solutions across the Business Line.
• Facilitate and monitor AI solutions development and execution phases with all stakeholders.
• Develop Generative AI cases for Safety, Environment, Operations, and Maintenance.
• Apply statistical analysis methods to test hypotheses and validate results based on the project or use-case.
• Build and train machine learning models to solve specific problems and optimize models for performance and accuracy such as anomaly detection algorithms or predictive models.
• Assess, identify, and mitigate key risks associated with cybersecurity and ensure that data practices adhere to the company's regulations and data privacy standards.
• Act as the Gas AI focal point of contact and coordinator with all other entities.

• The candidate must hold a Bachelor's degree in Engineering, Computer Science, Data Science and Analytics, Machine Learning, or AI, or in a related field from an accredited university. An advanced degree in an engineering discipline with a focus on machine learning, artificial intelligence, applied statistics, or operations research is desirable.
• 10 years of experience in building data analytics-based products or machine learning models.
• Able to program in different languages such as Python and has experience with statistics and data cleaning libraries and methodologies, in addition to visualization tools such as Power BI or Tableau.
• Strong knowledge in regression and classification, association rules & clustering, big data, databases & SQL, textual analysis (NLP), neural networks, and advanced visualization. Understanding of statistical and predictive and optimization algorithms is required.
• Analytical and problem-solving skills to derive insights and opportunities from data.
• Basic project management skills to plan, execute, and deliver data science projects.
• Past experience in leading AI solution deployment projects for Oil and Gas is preferable.
• Knowledge of plant automation systems, standard real-time interfaces such as OPC, and process historians such as PI is desirable.

Working environment

Our high-performing employees are drawn by the challenging and rewarding professional, technical, and industrial opportunities we offer, and are remunerated accordingly.

At Aramco, our people work on truly world-scale projects, supported by investment in capital and technology that is second to none. And because, as a global energy company, we are faced with addressing some of the world's biggest technical, logistical, and environmental challenges, we invest heavily in talent development.

We have a proud history of educating and training our workforce over many decades. Employees at all levels are encouraged to improve their sector-specific knowledge and competencies through our workforce development programs - one of the largest in the world.

Job ID: 15053

Tagged as: Gas Ventures Dept

• Analyze telecom data to identify trends, patterns, and anomalies using data stores such as SQL Server and Cloudera over Hive
• Develop and implement predictive models to improve customer experience and network performance
• Design, build, and maintain scalable data science pipelines
• Collaborate with cross-functional teams to understand business needs and deliver data-driven solutions
• May participate in optimizing data pipelines, queries, and processes to improve performance and efficiency
• Ensure data quality and integrity throughout the data lifecycle
• Knowledge API exposure and consumption over Dataiku/Python is preferred if possible
• Stay updated with the latest developments in data science technologies and best practices
  
  

• Bachelor's degree in Data Science, Statistics, Mathematics, or a related field
• 3+ years of experience in data analysis or data science in the telecommunications industry
• Knowledge of CRISP-DM methodology
  
  

• Proficiency in SQL, Python is a must while cloudera and MLOps frameworks is a plus
• Strong statistical analysis and modeling skills
• Experience with big data technologies (Hadoop, Cloudera, Spark)
• Knowledge in Geospatial and GIS data analysis and visualization and dealing with GIS files (KQL/KML)
• Familiarity of REST API development which is preferred to be done on Dataiku
• RAG/LLM knowledge
• NLP and Classical Machine Learning Knowledge
  
  

• Proficiency or Certification in Dataiku
• Local GCC experience, preferably Saudi projects
• Experience in the telecommunications industry