deep learning engineer

Jorofy Private Limited

We are seeking a highly skilled Senior AI Engineer (PhD) to lead the design, development, and deployment of advanced Artificial Intelligence and Machine Learning solutions. The ideal candidate will possess a PhD in Artificial Intelligence, Machine Learning, Computer Science, Data Science, or a related field, along with extensive industry experience in developing AI-driven products, conducting research, and translating innovative concepts into scalable enterprise solutions.The role requires expertise in Generative AI, Large Language Models (LLMs), Deep Learning, Natural Language Processing (NLP), Computer Vision, and MLOps practices.Key ResponsibilitiesAI Research &amp; Innovation<ul><li>Conduct advanced research in Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI.</li><li>Evaluate emerging AI technologies, frameworks, and methodologies to enhance organizational capabilities.</li><li>Publish research findings, technical papers, patents, or contribute to industry thought leadership initiatives.</li><li>Lead proof-of-concept (PoC) development for innovative AI solutions.</li></ul>Solution Design &amp; Development<ul><li>Architect and develop scalable AI/ML models and intelligent systems.</li><li>Design and optimize Large Language Model (LLM)-based applications and AI agents.</li><li>Build and fine-tune machine learning and deep learning models for production environments.</li><li>Develop AI-powered applications involving NLP, Computer Vision, Predictive Analytics, and Recommendation Systems.</li><li>Integrate AI solutions with enterprise platforms, APIs, and cloud environments.</li></ul>Generative AI &amp; LLM Engineering<ul><li>Develop and optimize Retrieval-Augmented Generation (RAG) architectures.</li><li>Fine-tune foundation models and implement prompt engineering strategies.</li><li>Design AI agents, autonomous workflows, and conversational AI solutions.</li><li>Implement vector databases and semantic search frameworks.</li><li>Evaluate model performance, accuracy, safety, and responsible AI practices.</li></ul>MLOps &amp; Deployment<ul><li>Build end-to-end ML pipelines for model training, deployment, monitoring, and maintenance.</li><li>Implement CI/CD processes for AI applications.</li><li>Optimize model performance, scalability, and infrastructure costs.</li><li>Monitor model drift and ensure continuous improvement.</li></ul>Leadership &amp; Collaboration<ul><li>Provide technical leadership and mentorship to AI Engineers, Data Scientists, and ML Engineers.</li><li>Collaborate with business stakeholders to identify AI opportunities and define solution roadmaps.</li><li>Participate in strategic technology planning and AI transformation initiatives.</li><li>Review code, architecture, and technical deliverables to ensure quality standards.</li></ul>Required QualificationsEducation<ul><li>PhD in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Mathematics, Statistics, or a related discipline.</li></ul>Experience<ul><li>8+ years of experience in AI/ML development, including research and production deployment.</li><li>Proven experience leading AI projects in enterprise environments.</li><li>Experience working with Generative AI, LLMs, and advanced deep learning architectures.</li></ul>Technical SkillsProgramming<ul><li>Python (Advanced)</li><li>SQL</li><li>Java, C++, or Scala (Preferred)</li></ul>AI/ML Frameworks<ul><li>PyTorch</li><li>TensorFlow</li><li>Keras</li><li>Scikit-learn</li><li>Hugging Face Transformers</li></ul>Generative AI &amp; LLM Technologies<ul><li>OpenAI APIs</li><li>LangChain</li><li>LangGraph</li><li>LlamaIndex</li><li>RAG Architectures</li><li>Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS)</li></ul>Cloud Platforms<ul><li>AWS</li><li>Microsoft Azure</li><li>Google Cloud Platform (GCP)</li></ul>MLOps &amp; DevOps<ul><li>Docker</li><li>Kubernetes</li><li>MLflow</li><li>Kubeflow</li><li>Jenkins</li><li>GitHub Actions</li></ul>Databases<ul><li>PostgreSQL</li><li>MongoDB</li><li>Vector Databases</li></ul>Preferred Qualifications<ul><li>Publications in reputed journals or AI conferences (NeurIPS, ICML, ICLR, ACL, CVPR, etc.).</li><li>Experience in Agentic AI, Autonomous Systems, and Multi-Agent Frameworks.</li><li>Knowledge of AI Governance, Responsible AI, Explainable AI (XAI), and AI Security.</li><li>Industry certifications in Cloud, AI, or Machine Learning technologies.</li></ul>Core Competencies<ul><li>Strategic Thinking</li><li>Research &amp; Innovation</li><li>Problem Solving</li><li>Leadership &amp; Team Mentoring</li><li>Stakeholder Management</li><li>Communication &amp; Presentation Skills</li><li>Analytical Thinking</li><li>Project Management</li></ul>Key Deliverables<ul><li>Production-ready AI and Generative AI solutions.</li><li>Scalable machine learning pipelines and architectures.</li><li>AI research initiatives and innovation roadmaps.</li><li>Performance optimization and continuous model improvement.</li><li>Technical mentorship and knowledge-sharing across teams.</li></ul>Experience Required: 8&ndash;15+ Years Education: PhD (Mandatory) Level: Senior / Lead Individual Contributor or Technical Lead Role.Education:<ul><li>Master's (Preferred)</li></ul>Experience:<ul><li>Senior Engineer: 10 years (Required)</li></ul>Work Location: In person

Senior AI Engineer (PhD)

Dezzex

Who we are?Dezzex uses Artificial Intelligence and Machine Learning technologies to advance the motor insurance industry by creating a system to automate claims. We use these technologies to improve insurance processes, reduce operational costs and enable a seamless customer experience. Our solution offering is also designed for the insurance companies, Insurance companies, Smart cities application.For applying as a Sr. Machine Learning Engineer, the person should have overall 7-8 years of experience out of which 4-5 years of experience should be in Machine &amp; Deep Machine learning. Especially using Convolution Neural Network (CNN), Image Analytics TensorFlow, Open CV etc.For applying as just a data scientist (Junior), the person needs to have experience of 3 - 9 years.With our fast-growing data scientist's team, we are looking to hire self-motivated smart individuals who are willing to take challenges in the field of Al image &amp; video analytics &amp; machine learning.Responsibilities:The Machine &amp; Deep Machine Learning Software Engineer (Expertise in Computer Vision) will be an early member of a growing team with responsibilities for designing and developing highly scalable machine learning solutions that impact many areas of our business.The individual in this role will help in the design and development of Neural Network (especially Convolution Neural Networks) &amp; ML solutions based on our reference architecture which is underpinned by big data &amp; cloud technology, micro-service architecture and high performing compute infrastructure.Typical daily activities include contributing to all phases of algorithm development including ideation, prototyping, design, and development production implementation.Required Skills:An ideal candidate will have background in software engineering and data science with expertise in machine learning algorithms, statistical analysis tools, and distributed systems.Experience in building machine learning applications, and broad knowledge of machine learning APIs, tools, and open source librariesStrong coding skills and fundamentals in data structures, predictive modelling and big data concepts Experience in designing full stack ML solutions in a distributed compute environmentExperience working with Python, Tensor Flow, Kera's, Sci-kit, pandas, NumPy, AZURE, AWS GPU Excellent communication skills with multiple levels of the organizationPay: AED10,000.00 - AED20,000.00 per monthExperience:<ul><li>ML: 3 years (Required)</li><li>Development: 5 years (Required)</li></ul>Language:<ul><li>Arabic (Preferred)</li></ul>Work Location: In person

Sr. Machine learning engineer.

DocuSketch

<div>
 
 The fastest-growing European SaaS company is searching for an
 
 AI/ML Engineer!
 
 
 
 ⚠️
 
 Before you apply:
 
 
 
 We require
 
 real 3D experience
 
 &mdash; meaning actual project work, not just listed skills. If 3D does not appear in your actual work history, this role is not for you.
 
 
 Applications that don't meet these criteria will be automatically rejected and may limit your eligibility for other DocuSketch roles.
 
 
 
 
 
 
 About DocuSketch:
 
 
 
 DocuSketch, with its European Headquarters in Potsdam, Germany, is a leading European software technology provider for the digital real estate economy. With our product brands Immoviewer and DocuSketch, we have become one of the most successful and fastest-growing software vendors in the rapidly expanding property tech sector. Our enthusiastic customer base is located across Europe and North America. DocuSketch's groundbreaking digital technology greatly facilitates real estate companies and building restoration companies to digitize, visualize, and virtualize real estate properties. Our solutions help our clients realize tremendous cost-saving potentials, process optimization, and revenue growth.
 
 
 
 
 
 You&rsquo;ll be working in a team that drives the company's AI development to develop algorithms for a variety of different use cases. This includes, e.g., working with equirectangular, phone, or satellite images to detect doors, windows, or other objects inside of buildings or finding facets on the roof. You&rsquo;ll be challenged by solving complex 3D geometry problems and working closely with our labeling team to ensure the best possible data quality.
 
 
 
 
 
 
 Responsibilities and Duties
 
 
 
 &middot; Research, train and deploy state-of-the-art machine learning models for object detection and 3D perception on equirectangular images
 
 
 &middot; Quickly prototype new ideas/technologies to create proof of concept and demos
 
 
 
 
 
 
 Qualifications
 
 
 
 &middot; Bachelor&rsquo;s Degree in Computer Science or equivalent experience
 
 
 &middot; Excellent math skills
 
 
 &middot; Experience with 3D computer vision algorithms
 
 
 &middot; Preferably 5+ years of experience developing and training machine learning models
 
 
 &middot; Strong Experience with Deep ML frameworks (PyTorch)
 
 
 &middot; Strong Experience in Python
 
 
 &middot; Self-motivated and energetic team player with a strong work ethic and cooperative attitude
 
 
 &middot; Excellent communication and organizational skills
 
 
 
 
 
 
 Plus
 
 
 
 &middot; Familiarity with building big data systems
 
 
 &middot; Training very large models using multiple GPUs in the cloud
 
 
 &middot; Experience with training machine learning models on equirectangular images
 
 
 
 
 
 We are seeking a performance-driven, high-energy personality who has several years of experience in the field. Since you will work intensely with teams from many countries, a solid command of the English language is a prerequisite. We offer attractive compensation, unlimited career opportunities, and the possibility to work in one of the most exciting software companies in the industry. Our headquarters are in Berlin, Germany, with major offices in Belgrade, Serbia, Lakeland, Florida, and in Canada.
 
 
 
 
 
 We look forward to receiving your application!
 
</div>

AI/ML Engineer

INNOBAYT INNOVATIVE SOLUTIONS

About the RoleInnobayt is seeking a highly motivated AI Engineer Intern for a 3-month intensive internship. During this program, you'll gain hands-on experience working on real-world AI projects involving Machine Learning, Large Language Models (LLMs), AI Agents, Retrieval-Augmented Generation (RAG), and Computer Vision. You'll collaborate closely with our experienced engineering team to develop innovative and impactful AI solutions.Key Responsibilities<ul><li>Assist in developing, fine-tuning, and optimizing machine learning models.</li><li>Build AI-powered solutions, including AI Agents and LLM-based applications.</li><li>Prepare and preprocess datasets for AI model development.</li><li>Research and experiment with LLMs, RAG, prompt engineering, and emerging AI technologies.</li><li>Integrate AI models into applications, APIs, and production workflows.</li><li>Evaluate, test, and improve AI model performance.</li><li>Collaborate with the engineering team on real-world AI projects.</li><li>Document technical work, experiments, and project progress.</li></ul>What We're Looking for Technical Skills<ul><li>Bachelor's degree (or final-year student) in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field. Fresh graduates are encouraged to apply.</li><li>Proficiency in Python and familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face.</li><li>Basic understanding of Machine Learning, Deep Learning, Natural Language Processing (NLP), or Computer Vision.</li><li>Familiarity with LLMs, embeddings, vector databases, RAG, LangChain, or OpenAI APIs is an advantage.</li><li>Basic knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) is a plus.</li></ul>Language Requirement<ul><li>Fluent in Arabic (required)</li><li>Fluent in English (required)</li></ul>Mindset &amp; Work Approach<ul><li>Passion for Artificial Intelligence and emerging technologies.</li><li>Eagerness to learn, experiment, and solve real-world challenges.</li><li>Strong analytical, problem-solving, and communication skills.</li><li>Ability to work effectively in a collaborative and fast-paced environment.</li></ul>What We Offer<ul><li>Hands-on experience working on real-world AI projects.</li><li>Mentorship from experienced AI and software engineers.</li><li>Exposure to modern AI tools, frameworks, and industry best practices.</li><li>A nominal monthly stipend (the exact amount will be discussed during the interview).</li><li>Internship certificate upon successful completion.</li><li>Opportunity for a full-time role based on performance.</li></ul>Job Type: InternshipWork Location: In person

AI Engineer Intern – 3-Month Internship

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
 <ul>
 <li>
 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
 </li>
 <li>
 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
 </li>
 <li>
 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
 </li>
 <li>
 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
 <ul>
 <li>
 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
 </li>
 <li>
 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
 </li>
 <li>
 Ensure platform reliability through monitoring, alerting, and structured incident response.
 </li>
 </ul>
 
 
 
 
 
 AI/ML &amp; Analytics Enablement
 
 
 <ul>
 <li>
 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
 </li>
 <li>
 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
 </li>
 <li>
 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
 <ul>
 <li>
 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
 </li>
 <li>
 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
 </li>
 <li>
 Support regulatory, ethical, and internal compliance obligations across the data estate.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Cost Discipline
 
 
 <ul>
 <li>
 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
 </li>
 <li>
 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Technical Leadership
 
 
 <ul>
 <li>
 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
 </li>
 <li>
 Provide hands-on technical guidance and code review across the team.
 </li>
 <li>
 Translate business requirements into technical designs with clear delivery outcomes.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
 </li>
 <li>
 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
 </li>
 <li>
 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
 </li>
 <li>
 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
 </li>
 <li>
 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
 </li>
 <li>
 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
 </li>
 <li>
 Practical FinOps outcomes on cloud spend.
 </li>
 <li>
 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
 </li>
 <li>
 Excellent written and verbal communication skills across technical and business audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Direct experience of a Synapse Analytics to Databricks migration.
 </li>
 <li>
 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
 </li>
 <li>
 Familiarity with Power BI semantic models and enterprise BI governance.
 </li>
 <li>
 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
 </li>
 <li>
 Multi-entity, multi-country group exposure with mixed data residency considerations.
 </li>
 <li>
 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
 </li>
 </ul>
 
 
 
 
 
 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
 <ul>
 <li>
 
 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
 </li>
 </ul>
 
 
 Preferred (one or more):
 
 
 <ul>
 <li>
 
 Databricks Certified Machine Learning Professional
 
 </li>
 <li>
 
 Databricks Certified Generative AI Engineer Associate
 
 </li>
 <li>
 
 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
 </li>
 <li>
 
 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
 </li>
 <li>
 
 Microsoft Certified: Azure Solutions Architect Expert
 
 </li>
 <li>
 
 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
 </li>
 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
</div>

Data Platform Lead

HAO ARCHITECTURAL & ENGINEERING CONSULTANCY

<ul><li>Position Title: Senior Structural Engineer &ndash; High-Rise Specialists</li><li>Experience Required: Minimum 10+ years of post-graduation experience</li><li>Location: Dubai, UAE</li><li>Licensing Requirement: Dubai Municipality (DM) G+Unlimited License (Mandatory)</li></ul>We are looking for a high-caliber Senior Structural Engineer with a proven track record of delivering complex, iconic, high-rise buildings (40+ stories) in Dubai. The ideal candidate will combine deep technical expertise in advanced structural analysis with an ironclad understanding of local regulatory frameworks and a seamless ability to navigate local authority approvals.Key Responsibilities1. High-Rise Structural Design &amp; Engineering<ul><li>Lead the structural design, analysis, and optimization of complex high-rise residential, commercial, and mixed-use towers from concept stage through to detailed design and construction.</li><li>Perform complex calculations for lateral loads (wind and seismic analysis), deep foundations, post-tensioned slabs, and composite structures utilizing advanced engineering software.</li><li>Ensure all designs meet international best practices, international codes (ACI, ASCE, Eurocodes), and specific local amendments.</li></ul>2. Authority Approvals &amp; Regulatory Liaison<ul><li>Act as the primary technical point of contact and bridge between HAOarchitects and Dubai authority bodies.</li><li>Secure smooth, efficient structural approvals and building permits from Dubai Municipality (DM), Dubai Development Authority (DDA), and Trakhees (PCFC).</li><li>Proactively resolve technical comments or queries raised by authority engineers during the peer-review process to prevent project delays.</li></ul>3. Project Coordination &amp; Leadership<ul><li>Interactively coordinate with internal architectural teams, MEP engineers, and external project stakeholders to ensure fully integrated, constructible design packages.</li><li>Review, stamp, and sign off on structural drawings and design calculations as the registered G+Unlimited engineer of record.</li><li>Provide technical mentorship to junior and mid-level structural engineers within the firm, maintaining high standards of quality assurance.</li></ul>Candidate Profile &amp; QualificationsEducation &amp; Licensure<ul><li>Bachelor&rsquo;s Degree in Civil or Structural Engineering from a recognized, accredited institution (Master&rsquo;s degree preferred).</li><li>Dubai Municipality G+Unlimited Certification is an absolute, non-negotiable requirement.</li></ul>Technical &amp; Professional Experience<ul><li>10+ years of robust structural engineering experience, with a minimum of 5&ndash;7 years spent actively delivering high-rise projects within the Emirate of Dubai.</li><li>Demonstrated history of successfully obtaining structural clearances and permits across DM, DDA, and Trakhees portals.</li><li>Deep knowledge of the Dubai Building Code (DBC), seismic parameters, and local soil/geotechnical conditions.</li><li>Mastery of industry-standard structural analysis software (e.g., ETABS, SAFE, SAP2000, STAAD.Pro) and strong familiarity with BIM workflows (Revit).</li></ul>Core Competencies<ul><li>Authority Savvy: A sophisticated understanding of how to package, present, and defend structural designs to local authorities to expedite approvals.</li><li>Problem Solving: Ability to value-engineer structural solutions to save client resources without compromising safety or architectural intent.</li><li>Communication: Exceptional verbal and written communication skills in English, with the gravitas to represent the firm in high-stakes technical meetings.</li></ul>Education:<ul><li>Bachelor's (Required)</li></ul>Experience:<ul><li>Dubai: 10 years (Required)</li></ul>License/Certification:<ul><li>G + Unlimited Certificate from Dubai Municipality (Required)</li><li>Dubai Driving License (Required)</li></ul>Work Location: In person

Sr. Structural Engineer

Ministry of Economy & Tourism

<div>
 
 
 الهدف العام للوظيفة
 
 
 
 خبير في الذكاء الاصطناعي ضمن قسم الذكاء الاصطناعي في الوزارة، يتولى ضمان نشر أنظمة الذكاء الاصطناعي بصورة فعّالة وأخلاقية وقابلة للتوسع عبر عمليات الوزارة. يجسّر هذا الدور الفجوة بين القدرات التقنية للذكاء الاصطناعي والاحتياجات المؤسسية الحيوية، من خلال الإشراف البشري المتمحور حول الإنسان وحوكمة الأنظمة وتحسينها المستمر. يجمع هذا المنصب بين العمق التقني ومعرفة الأعمال وإدارة أصحاب المصلحة وقيادة التغيير لضمان استدامة تطبيقات الذكاء الاصطناعي وتحقيقها لقيمة مؤسسية قابلة للقياس
 
 
 
 المسؤوليات الرئيسية
 
 
 <ul>
 <li>
 تحديد متطلبات البيانات الجاهزة للذكاء الاصطناعي والإشراف عليها بما يشمل بيانات التدريب وبيانات الإدخال التشغيلية ونماذج القرار، وضمان جودتها واتساقها.
 </li>
 <li>
 تصميم وإدارة سير عمل الإشراف البشري-الآلي (Human-in-the-Loop) للتحقق من مخرجات الذكاء الاصطناعي قبل النشر التشغيلي.
 </li>
 <li>
 مراقبة دقة نماذج الذكاء الاصطناعي ومستويات الثقة والكشف عن انحراف الأداء للحفاظ على الفاعلية التشغيلية وضمان الاستمرارية.
 </li>
 <li>
 اختبار وكلاء الذكاء الاصطناعي وتدريبهم من خلال آليات التغذية الراجعة وهندسة الطلبات وبروتوكولات التعلم الخاضع للإشراف.
 </li>
 <li>
 تطوير وتطبيق أطر حوكمة الذكاء الاصطناعي والمبادئ التوجيهية الأخلاقية وسياسات الامتثال المتوافقة مع اللوائح الحكومية المعتمدة.
 </li>
 <li>
 المشاركة في تصنيف تطبيقات الذكاء الاصطناعي حسب مستوى مخاطرها وتأثيرها، وإرساء معايير رقابة متدرجة تتناسب مع درجة خطورة كل تطبيق.
 </li>
 <li>
 قيادة الإشراف على الموردين وحوكمة العقود لضمان السلطة التقنية والشفافية ومنع الاحتكار التقني من قِبل الموردين.
 </li>
 <li>
 تحديد مخاطر الذكاء الاصطناعي والتخفيف منها بما تشمل عدم موضوعية النموذج في نتائجه، ومحاولات التلاعب بالنموذج، وإفساد بيانات التدريب، وتراجع أداء النماذج بمرور الوقت.
 </li>
 <li>
 تصميم وقيادة برامج التثقيف في الذكاء الاصطناعي للمطورين والمستخدمين وأصحاب المصلحة المتأثرين بتطبيقات الذكاء الاصطناعي عبر الوزارة.
 </li>
 <li>
 إرشاد فرق العمل المشتركة وتنسيق التعاون متعدد التخصصات بين فرق تطوير الحلول والهندسة والتشغيل والأعمال.
 </li>
 <li>
 ترجمة القدرات والقيود التقنية لأنظمة الذكاء الاصطناعي إلى توصيات عملية وتوجيهات واضحة تُمكّن الإدارة وأصحاب المصلحة من اتخاذ قرارات مدروسة.
 </li>
 <li>
 تحديد مؤشرات أداء نماذج الذكاء الاصطناعي ومتابعتها بما تشمل نسبة الدقة، ودرجة يقين النموذج، ومعدلات قبول المخرجات، ومؤشرات انحراف الأداء، وإعداد التقارير الدورية.
 </li>
 <li>
 إدارة حلقات التغذية الراجعة من مستخدمي الذكاء الاصطناعي والفرق التشغيلية لتحسين النماذج والعمليات باستمرار.
 </li>
 <li>
 تحديد حالات استخدام الذكاء الاصطناعي الناشئة والتوصية بتحسينات على سير العمل والواجهات لتحقيق أقصى قيمة مؤسسية.
 </li>
 <li>
 دعم التوسع في نشر تطبيقات الذكاء الاصطناعي عبر الوزارة من خلال توحيد المعايير، وبناء قوالب وأدوات جاهزة قابلة لإعادة الاستخدام، وتوثيق أفضل الممارسات لضمان الاتساق والكفاءة.
 </li>
 <li>
 التعامل مع عزوف الموظفين وترددهم في تبني الذكاء الاصطناعي من خلال ربط تطبيقاته بواقع عمل كل فريق، وبناء الثقة، وتعزيز الانفتاح لتسريع تبني الحلول الذكية.
 </li>
 <li>
 بناء شبكات تبادل المعرفة والخبرات في مجال الذكاء الاصطناعي عبر الجهات الحكومية، وتعزيز التعاون ومشاركة أفضل الممارسات بين الكوادر المتخصصة.
 </li>
 <li>
 التحقق من مخرجات نماذج الذكاء الاصطناعي وتحديد الحالات الحدية والاستثنائية، وتطبيق الحكم البشري المدروس في القرارات المعقدة لضمان موثوقية الأنظمة ودقتها.
 </li>
 <li>
 تنفيذ أي مهام أخرى يكلف بها رئيس القسم في نطاق اختصاصه.
 </li>
 </ul>
 
 
 المؤهلات والخبرة
 
 
 <ul>
 <li>
 دكتوراه - علوم الحاسب / الذكاء الاصطناعي / هندسة / إحصاء أو ما يعادلها (بدون خبرة)
 </li>
 <li>
 ماجستير - علوم الحاسب / الذكاء الاصطناعي / علوم البيانات / هندسة أو ما يعادلها (3 سنوات خبرة)
 </li>
 <li>
 بكالوريوس - علوم الحاسب / الذكاء الاصطناعي / هندسة الحاسوب / إحصاء أو ما يعادلها (7 سنوات خبرة)
 </li>
 </ul>
 
 
 الشهادات المهنية
 
 
 <ul>
 <li>
 شهادة معتمدة في الذكاء الاصطناعي وتعلم الآلة على المنصات السحابية مثل Google Cloud Professional ML Engineer / AWS Machine Learning Specialty / Microsoft Azure AI Engineer Associate
 </li>
 <li>
 شهادة في نماذج اللغة الكبيرة وهندسة الطلبات مثل DeepLearning.AI Generative AI / Prompt Engineering Specialization
 </li>
 <li>
 شهادة في حوكمة الذكاء الاصطناعي وأخلاقياته مثل IAPP AI Governance Professional / ISO 42001 Lead Implementer)
 </li>
 <li>
 شهادة في علوم البيانات وهندستها مثل IBM Data Science Professional / Databricks Data Engineer Associate)
 </li>
 <li>
 شهادة في تشغيل نماذج الذكاء الاصطناعي مثل MLflow MLOps Certified / Kubeflow Practitioner / DataRobot MLOps
 </li>
 <li>
 شهادة في أمن الذكاء الاصطناعي والهجمات المعادية مثل Certified AI Security Professional / OWASP AI Security
 </li>
 <li>
 شهادة في إدارة المشاريع وقيادة التغيير أو ما يعادلها PMP / PRINCE2 / Prosci Change Management
 </li>
 <li>
 دورة في تصميم سير العمل الإنساني-الآلي (Human-in-the-Loop) واختبار النماذج وتقييم الانجراف
 </li>
 <li>
 دورة في بنية بيانات الذكاء الاصطناعي ورسم خرائط المعرفة (Knowledge Graphs / Data Mapping)
 </li>
 <li>
 دورة في قياس أداء نماذج الذكاء الاصطناعي ومؤشرات الدقة ومعدلات القبول
 </li>
 <li>
 دورة في أساسيات أمن المعلومات وحماية البيانات في بيئات الذكاء الاصطناعي الحكومية
 </li>
 </ul>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Job Purpose
 
 
 
 Serve as an Artificial Intelligence (AI) expert within the Ministry's AI Department, responsible for ensuring the effective, ethical, and scalable deployment of AI systems across the Ministry's operations. This role bridges the gap between AI technical capabilities and critical business needs through human-centered oversight, AI governance, and continuous optimization. The position combines deep technical expertise with business knowledge, stakeholder management, and change leadership to ensure AI applications remain sustainable and deliver measurable organizational value.
 
 
 
 Key Responsibilities
 
 
 <ul>
 <li>
 Define and oversee AI-ready data requirements, including training datasets, operational input data, and decision models, while ensuring data quality, consistency, and integrity.
 </li>
 <li>
 Design and manage Human-in-the-Loop (HITL) workflows to validate AI outputs before operational deployment.
 </li>
 <li>
 Monitor AI model accuracy, confidence levels, and performance drift to maintain operational effectiveness and ensure service continuity.
 </li>
 <li>
 Test and train AI agents using feedback mechanisms, prompt engineering, and supervised learning protocols.
 </li>
 <li>
 Develop and implement AI governance frameworks, ethical guidelines, and compliance policies aligned with approved government regulations.
 </li>
 <li>
 Participate in classifying AI applications according to their risk and impact levels and establish proportionate control measures based on the level of risk.
 </li>
 <li>
 Lead vendor oversight and contract governance to ensure technical ownership, transparency, and prevent vendor lock-in.
 </li>
 <li>
 Identify and mitigate AI-related risks, including model bias, adversarial attacks, training data poisoning, and model performance degradation over time.
 </li>
 <li>
 Design and lead AI awareness and education programs for developers, end users, and stakeholders affected by AI implementations across the Ministry.
 </li>
 <li>
 Guide cross-functional teams and coordinate multidisciplinary collaboration among solution development, engineering, operations, and business teams.
 </li>
 <li>
 Translate the technical capabilities and limitations of AI systems into practical recommendations and clear guidance to support informed decision-making by management and stakeholders.
 </li>
 <li>
 Define and monitor AI model performance metrics, including accuracy rates, confidence scores, output acceptance rates, and model drift indicators, and prepare periodic performance reports.
 </li>
 <li>
 Manage feedback loops from AI users and operational teams to continuously improve AI models and business processes.
 </li>
 <li>
 Identify emerging AI use cases and recommend workflow and user interface enhancements to maximize organizational value.
 </li>
 <li>
 Support the enterprise-wide scaling of AI applications by standardizing practices, developing reusable templates and tools, and documenting best practices to ensure consistency and efficiency.
 </li>
 <li>
 Address employee resistance and hesitation toward AI adoption by aligning AI solutions with team-specific business needs, building trust, and promoting openness to accelerate the adoption of intelligent solutions.
 </li>
 <li>
 Build knowledge-sharing networks and AI communities of practice across government entities, fostering collaboration and the exchange of best practices among AI professionals.
 </li>
 <li>
 Validate AI model outputs, identify edge cases and exceptional scenarios, and apply sound human judgment in complex decision-making to ensure the reliability and accuracy of AI systems.
 </li>
 <li>
 Perform any other duties assigned by the Head of the AI Department within the scope of the role.
 </li>
 </ul>
 
 
 Qualifications &amp; Experience
 
 
 <ul>
 <li>
 PhD in Computer Science, Artificial Intelligence, Engineering, Statistics, or a related field (no experience required).
 </li>
 <li>
 Master's Degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field (minimum 3 years of relevant experience).
 </li>
 <li>
 Bachelor's Degree in Computer Science, Artificial Intelligence, Computer Engineering, Statistics, or a related field (minimum 7 years of relevant experience).
 </li>
 </ul>
 
 
 Professional Certifications
 
 
 <ul>
 <li>
 Professional certification in Artificial Intelligence and Machine Learning on cloud platforms, such as
 
 Google Cloud Professional Machine Learning Engineer
 
 ,
 
 AWS Machine Learning Specialty
 
 , or
 
 Microsoft Azure AI Engineer Associate
 
 .
 </li>
 <li>
 Certification in Large Language Models (LLMs) and Prompt Engineering, such as
 
 DeepLearning.AI Generative AI Specialization
 
 or
 
 Prompt Engineering Specialization
 
 .
 </li>
 <li>
 Certification in AI Governance and Ethics, such as
 
 IAPP AI Governance Professional (AIGP)
 
 or
 
 ISO/IEC 42001 Lead Implementer
 
 .
 </li>
 <li>
 Certification in Data Science and Data Engineering, such as
 
 IBM Data Science Professional Certificate
 
 or
 
 Databricks Data Engineer Associate
 
 .
 </li>
 <li>
 Certification in AI Operations (MLOps), such as
 
 MLflow MLOps Certified
 
 ,
 
 Kubeflow Practitioner
 
 , or
 
 DataRobot MLOps
 
 .
 </li>
 <li>
 Certification in AI Security and Adversarial AI, such as
 
 Certified AI Security Professional
 
 or
 
 OWASP AI Security
 
 .
 </li>
 <li>
 Certification in Project Management and Change Leadership, such as
 
 PMP
 
 ,
 
 PRINCE2
 
 , or
 
 Prosci Change Management
 
 .
 </li>
 <li>
 Training course in
 
 Human-in-the-Loop (HITL)
 
 workflow design, AI model testing, and model drift evaluation.
 </li>
 <li>
 Training course in AI data architecture, data mapping, and knowledge graphs.
 </li>
 <li>
 Training course in AI model performance measurement, including accuracy metrics, confidence scores, and output acceptance rates.
 </li>
 <li>
 Training course in information security fundamentals and data protection in government AI environments.
 </li>
 </ul>
 
 
 
</div>

خبير الذكاء الاصطناعي - Artificial Intelligence Expert

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