145 Feature Engineering jobs in Saudi Arabia
Data Analysis Specialist
Posted today
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Job Purpose - الغرض من الوظيفة
The Data Analyst will play a key role in improving the quality of patient safety data at the Saudi Patient Safety Center (SPSC). By applying advanced statistical and analytical methods, the analyst will generate evidence-based reports, develop national patient safety KPIs, and support decision-making at both national and international levels - سيساهم محلل البيانات بدور محوري في تحسين جودة بيانات سلامة المرضى في المركز السعودي لسلامة المرضى ومن خلال تطبيق الأساليب الإحصائية والتحليلية المتقدمة، سيقوم المحلل بإعداد تقارير قائمة على الأدلة، وتطوير مؤشرات أداء وطنية لسلامة المرضى، ودعم عملية اتخاذ القرار على المستويين الوطني والدولي. ويسهم هذا الدور بشكل مباشر في تعزيز مكانة المركز كجهة وطنية رائدة ذات شراكات دولية ومعترف بها من قبل منظمة الصحة العالمية (WHO).
Responsibilities - المسؤوليات
- Collect, clean, analyze, and present findings of healthcare data using advanced statistical tools and methods - جمع البيانات الصحية وتنظيفها وتحليلها وعرض نتائجها باستخدام أدوات وأساليب إحصائية متقدمة.
- Prepare reports highlighting trends, risks, and recommendations for performance improvement - إعداد تقارير تسلط الضوء على الاتجاهات والمخاطر والتوصيات اللازمة لتحسين الأداء.
- Collaborate with clinical teams to interpret findings and implement evidence-based improvements - التعاون مع الفرق السريرية لتفسير النتائج وتطبيق التحسينات المبنية على الأدلة.
- Support research studies and national/international projects related to patient safety - دعم الدراسات البحثية والمشاريع الوطنية والدولية ذات الصلة بسلامة المرضى.
- Develop, monitor, and evaluate patient safety Key Performance Indicators (KPIs) - تطوير ومتابعة وتقييم مؤشرات الأداء الرئيسة (KPIs) الخاصة بسلامة المرضى.
- Ensure accuracy, integrity, and quality assurance of data before reporting - ضمان دقة ونزاهة البيانات وجودتها قبل نشرها أو الإبلاغ عنها.
- Contribute to strengthening SPSC's international reporting and benchmarking in line with WHO standards - الإسهام في تعزيز التقارير الدولية والمقارنات المرجعية للمركز بما يتماشى مع معايير منظمة الصحة العالمية.
- Create dashboards and visualization tools (Power BI/Tableau) to facilitate decision-making in patient safety - إنشاء لوحات متابعة وأدوات عرض بيانية (Power BI/Tableau) لدعم عملية اتخاذ القرار في مجال سلامة المرضى.
Requirement and Qualifications - المتطلبات والمؤهلات
- Bachelor or Master's degree in Biostatistics, Epidemiology, Health Data Science, or a related field - درجة الباكلوريوس او الماجستير في الإحصاء الحيوي، علم الأوبئة، علوم بيانات الصحة، أو مجال ذي صلة.
- Minimum of 4 years' experience in biostatistics or healthcare data analysis, Experience in patient safety data domains is preferred.
- Patient Safety certification - شهادة في سلامة المرضى.
- Certified Professional in Healthcare Quality (CPHQ) - أخصائي معتمد في جودة الرعاية الصحية
- Machine Learning specialization - تخصص في التعلم الآلي.
- Lean Six Sigma Green/Black Belt - لين سقما
- Certified Health Data Analyst (CHDA) - محلل بيانات صحية معتمدة
Skills - المهارات
Technical Skills:
- Proficiency in statistical software and tools such as SAS, R, SPSS, Power BI, or Python - إجادة استخدام البرمجيات والأدوات الإحصائية مثل SAS، R، SPSS، Power BI أو Python.
- Strong SQL and data querying from relational databases or cloud-based environments - إتقان SQL واستخراج البيانات من قواعد البيانات العلائقية أو البيئات السحابية.
- Advanced analytical and problem-solving skills, with ability to extract meaningful insights - مهارات تحليلية متقدمة وحل المشكلات مع القدرة على استنتاج رؤى ذات مغزى.
- Strong reporting skills with ability to communicate complex findings clearly - مهارات قوية في إعداد التقارير وعرض النتائج المعقدة بشكل واضح.
- Ensure data accuracy, quality, and security in compliance with internal policies and data governance standards - ضمان دقة وجودة وأمن البيانات بما يتماشى مع السياسات الداخلية ومعايير حوكمة البيانات.
- Cross-functional Collaboration - القدرة على التعاون الفعال مع فرق متعددة التخصصات.
Soft Skills:
- Strong communication and data presentation abilities for clinical and non-clinical audiences - قدرات تواصل متميزة وعرض البيانات بطريقة مناسبة للجمهور السريري وغير السريري.
- High attention to detail and accuracy in data work - دقة عالية واهتمام بالتفاصيل في العمل مع البيانات.
- Ability to collaborate effectively in multidisciplinary teams - القدرة على التعاون والعمل الجماعي بفعالية.
Data Analysis Specialist
Posted today
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Job Description
- Collect, clean, and transform structured and unstructured datasets from multiple sources (databases, APIs, data warehouses, and flat files) for analysis.
- Develop, maintain, and optimize SQL queries, stored procedures, and ETL pipelines to ensure reliable data flows.
- Perform statistical analysis, hypothesis testing, and predictive modeling to extract actionable insights and support decision-making.
- Create advanced dashboards and reports using tools such as Power BI, Tableau, or Looker, ensuring KPIs are tracked and visualized effectively.
- Collaborate with data engineers and business stakeholders to define data requirements and ensure alignment between technical outputs and business needs.
- Apply data mining, clustering, and regression techniques to detect patterns, trends, and anomalies across large datasets.
- Document methodologies, maintain reproducibility of analysis, and adhere to best practices for version control and code management (e.g., Git).
Job Requirements
- A degree in computer science, data science or any other relevant field. A master's is a plus
- 4 years of experience in relevant fields
- Data Engineering & Querying: Strong proficiency in SQL
- Visualization & Reporting: Advanced skills in BI tools (Power BI, Tableau, Looker, or equivalent) and ability to design performance-optimized dashboards.
- Data Wrangling: Ability to handle raw, messy data—cleaning, normalizing, feature engineering, and managing large datasets with performance considerations.
- Cloud & Analytics Tools: Familiarity with cloud platforms (GCP BigQuery, AWS Redshift, Azure Synapse) and distributed data systems (Spark, Hadoop) is a plus as well as hands-on experience on Dataiku is a plus.
Machine Learning
Posted today
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Machine Learning & AI Specialist
Location:
Dammam / Remote
Type:
Full-time
Objective:
Develop AI and computer vision solutions for fast and accurate item recognition and counting.
Responsibilities:
- Build and deploy computer vision models for SKU recognition in varied real-world settings.
- Implement 3D perception / Spatial Vision using
LiDAR
and other sensors for accurate mapping of items and shelves. - Optimize models for on-device processing (mobile/tablet) to reduce latency.
- Integrate AI outputs with backend or ERP systems for real-time inventory updates.
- Preprocess, label, and manage datasets for training and testing models.
- Continuously monitor and improve model accuracy and performance.
Required Skills & Tools:
- Deep learning & computer vision (CNNs, 3D CNNs, object detection)
- Frameworks:
TensorFlow, PyTorch, OpenCV - On-device inference:
TensorFlow Lite, ONNX, CoreML - 3D sensing / LiDAR integration
- Data preprocessing, labeling, and model evaluation
Preferred:
- Augmented Reality (AR) for overlay information
- Self-supervised or semi-supervised learning techniques
Machine Learning Engineer
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About the role
We are seeking a talented Machine Learning Engineer to join our growing team. As a Machine Learning Engineer, you will play a pivotal role in optimizing ML models for efficient training and inference, deploying deep learning models in specialized hardware for inference usage, monitoring the performance and latency of deployed models, and maintaining ML infrastructure.
What you'll do- Designing, building, supporting, and scaling our cloud and / or our on-premise ML infrastructure.
- Deploying deep learning models in production environments and optimizing their performance for inference on either GPU or CPU.
- Maintaining our infrastructure (on-prem and cloud) and preparing it for training and inference purposes.
- Monitoring deployed ML models for their performance, latency, and throughput using automated tools for monitoring and reporting.
- Evaluating and improving data science processes, identifying opportunities for automation, efficiency, and scalability.
- Collaborating with other teams, including product managers, data scientists, software engineers, data annotators, and business stakeholders, to ensure successful deployments of ML models.
- Staying up to date with the latest trends and advancements in ML engineering, ML models, and applying this knowledge to enhance the team's capabilities.
- Exploring and learning new technologies that can complement or replace our current stack to improve it.
- You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
- You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
- The fundamentals will be taken care of : competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best.
- You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
- We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.
Apply now
Qualifications- 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.
Machine Learning Engineer
Posted 5 days ago
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- Build and maintain high-performance microservices using Kotlin and Spring Boot
- Model relational schemas, optimize SQL queries, and manage data consistency across MySQL and PostgreSQL
- Collaborate with data scientists to consume ML models (e.g., via REST, gRPC), embed intelligent decisioning into backend services
- Develop and maintain RESTful APIs; define contracts for frontend, partner services, or AI inference layers
- Contribute to Docker/Kubernetes-based deployments, CI/CD pipelines, and monitoring (Grafana, Prometheus, etc.)
- 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
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Machine Learning Engineer
Posted 6 days ago
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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.
Machine Learning Specialist
Posted 12 days ago
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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.
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Machine Learning Engineer
Posted today
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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.
Machine Learning Engineer
Posted today
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Job Title: Machine Learning Engineer (AI/ML – Generative AI Focus)
Location: Riyadh, Saudi Arabia
Employment Type: Full-Time (Onsite)
Compensation: 15,000 SAR (Net) + 6,000 SAR (Benefits)
About the Role
We are seeking a highly skilled Machine Learning Engineer with strong expertise in LLMs, Generative AI, and modern ML frameworks. This role requires a professional who can design, build, and deploy machine learning systems, while also driving technical roadmaps and collaborating with business SMEs. Fluency in Arabic and residency in Riyadh are mandatory.
Key Responsibilities
Design, develop, and deploy machine learning models and pipelines for business-critical applications
Work hands-on with Large Language Models (LLMs), focusing on prompt engineering, Retrieval-Augmented Generation (RAG), and AI agents
Lead and guide engineering teams on technical strategies and roadmaps
Collaborate with business SMEs to translate requirements into ML/AI solutions
Implement and optimize end-to-end ML systems in production, ensuring scalability, reliability, and performance
Integrate solutions with cloud platforms (Azure, AWS, GCP)
Manage data preprocessing, feature engineering, and SQL-based transformations
Monitor, evaluate, and continuously improve model accuracy, fairness, and efficiency
Required Qualifications
5+ years of professional experience in building and deploying machine learning models and systems
1+ years of practical experience with LLMs and Generative AI techniques (prompt engineering, RAG, agents)
Proven experience in leading or mentoring engineering teams or driving technical roadmaps
Strong programming proficiency in Python
Hands-on expertise with LangChain or LangGraph
Advanced SQL skills for data handling and pipeline development
Experience with cloud services (Azure, GCP, or AWS)
Strong communication skills with the ability to collaborate effectively with business stakeholders
Must be a resident of Riyadh and fluent in Arabic (mandatory)
Preferred Skills (Nice-to-Have)
Experience with vector databases (Pinecone, FAISS, Weaviate, Milvus)
Familiarity with MLOps tools (MLflow, Kubeflow, Airflow)
Deep learning frameworks such as PyTorch, TensorFlow, Hugging Face Transformers
Experience in deploying AI solutions at scale
Why Join Us
Competitive package: 15,000 SAR net + 6,000 SAR benefits
Opportunity to work on cutting-edge Generative AI projects in Riyadh
Collaborative and innovative work culture
Machine Learning Engineer
Posted today
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Apt Resources is seeking an experienced Machine Learning Engineer for a client in Abu Dhabi's Government & Public Sector. In this role, you will design and deploy cutting-edge AI/ML solutions using Large Language Models (LLMs) like GPT, Llama, and BERT to drive innovation in public services.
This is an exciting opportunity to work on high-impact projects involving Retrieval-Augmented Generation (RAG), fine-tuning, and prompt engineering, ensuring secure, scalable, and compliant AI systems for government applications.
Key Responsibilities:- Develop and optimize AI/ML pipelines for LLMs, focusing on RAG architectures, fine-tuning, and prompt engineering tailored for public sector needs.
- Implement scalable solutions using Python, LangChain, HuggingFace, PyTorch/TensorFlow, and cloud-based ML services (Azure ML preferred).
- Integrate vector/graph databases (Weaviate, Neo4j) into production systems to enhance data retrieval and analysis.
- Deploy and monitor models in production, ensuring adherence to government security and compliance standards.
- Collaborate with cross-functional teams to align AI solutions with public sector objectives (e.g., citizen services, data governance, operational efficiency).
- 6-14 years of hands-on experience in AI/ML, with a strong focus on LLMs and GenAI.
- Expertise in LLM architectures (Transformers), prompt engineering, and RAG implementations.
- Proficiency in Python and ML frameworks (LangChain, LlamaIndex, HuggingFace, Scikit-learn).
- Experience with cloud platforms (Azure ML, AWS, or GCP) and MLOps tools (MLflow, model monitoring).
- Familiarity with vector databases, ETL pipelines, and unstructured data handling.
- Knowledge of government IT standards or secure deployments is a plus.
To be discussed