17 Lead Data Scientist jobs in Riyadh

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.

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.

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Mozn is a rapidly growing technology firm revolutionising the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia. We are working to realise Vision 2030 with a proven track record of excellence in supporting and growing the tech ecosystem in the GCC region. Mozn is the trusted AI technology partner for some of the largest government organizations and 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.

We are looking for a Senior Machine Learning Engineer to lead the design, deployment, and optimisation of machine learning and generative AI solutions. The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.

• Design, build, and scale machine learning models and infrastructure
• Deploy deep learning and generative models into production for public and private sector projects
• Collaborate with data scientists, product managers, and stakeholders to deliver AI-driven insights
• Optimise ML training and inference for performance, latency, and scalability
• Monitor, retrain, and improve deployed ML models
• Drive consultation efforts, providing expert guidance to client stakeholders

• Bachelor’s or master’s degree in computer science or related field
• 4+ years of experience in ML engineering, data science, and generative AI
• Strong track record of projects across public and private sectors
• Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks
• Expertise in containerisation and orchestration technologies (Docker, Kubernetes), with hands‑on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama)
• Skilled in on‑premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices
• Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimisation) and secure network configurations for internal AI services
• Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science)
• Familiarity with MLOps practices and automation pipelines

• 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

Mid‑Senior level

Full‑time

Engineering and Information Technology

Software Development

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

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 looking for a Senior Machine Learning Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.

• Designing, building, and scaling machine learning models and infrastructure
• Deploying deep learning and generative models into production for public and private sector projects
• Collaborating with data scientists, product managers, and stakeholders to deliver AI-driven insights
• Optimizing ML training and inference for performance, latency, and scalability
• Monitoring, retraining, and improving deployed ML models
• Driving consultation efforts, providing expert guidance to client stakeholders

• Bachelor’s or master’s degree in computer science or related field
• 4+ years of experience in ML engineering, data science, and generative AI
• Strong track record of projects across public and private sectors
• Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks
• Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama)
• Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices
• Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services
• Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science)
• Familiarity with MLOps practices and automation pipelines
• 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

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

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

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