Machine operator Jobs

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Requirements</span><ul><li><span>Minimum 3–5 years of experience as a Boom Truck Operator<br></span></li><li><span>Valid Qatar Heavy/Crane Driving License<br></span></li><li><span>Experience in lifting, loading &amp; unloading activities<br></span></li><li><span>Good knowledge of safe lifting and rigging practices<br></span></li><li><span>Must be available to join immediately with a valid QID.<br></span></li></ul><br> </div>

Role Overview:<br><br>Drive advanced analytics, predictive modeling, and machine learning initiatives to support business and operational decisions.<br><br>Key Responsibilities:<br><br>Develop predictive and statistical models Identify trends, anomalies, and optimization opportunities Translate data insights into actionable strategies Support deployment of analytics solutions<br><br>Requirements:<br><br>Master’s or PhD in Data Science, AI, or related field10–13+ years in advanced analytics Strong programming (Python, AI/ML frameworks)

Role Overview:<br><br>Drive advanced analytics, predictive modeling, and machine learning initiatives to support business and operational decisions.<br><br>Key Responsibilities:<br><br>Develop predictive and statistical models Identify trends, anomalies, and optimization opportunities Translate data insights into actionable strategies Support deployment of analytics solutions<br><br>Requirements:<br><br>Master’s or PhD in Data Science, AI, or related field10–13+ years in advanced analytics Strong programming (Python, AI/ML frameworks)

Role Overview:<br><br>Drive advanced analytics, predictive modeling, and machine learning initiatives to support business and operational decisions.<br><br>Key Responsibilities:<br><br>Develop predictive and statistical models Identify trends, anomalies, and optimization opportunities Translate data insights into actionable strategies Support deployment of analytics solutions<br><br>Requirements:<br><br>Master’s or PhD in Data Science, AI, or related field10–13+ years in advanced analytics Strong programming (Python, AI/ML frameworks)

Role Overview:<br><br>Drive advanced analytics, predictive modeling, and machine learning initiatives to support business and operational decisions.<br><br>Key Responsibilities:<br><br>Develop predictive and statistical models Identify trends, anomalies, and optimization opportunities Translate data insights into actionable strategies Support deployment of analytics solutions<br><br>Requirements:<br><br>Master’s or PhD in Data Science, AI, or related field10–13+ years in advanced analytics Strong programming (Python, AI/ML frameworks)

Role Overview:<br><br>Drive advanced analytics, predictive modeling, and machine learning initiatives to support business and operational decisions.<br><br>Key Responsibilities:<br><br>Develop predictive and statistical models Identify trends, anomalies, and optimization opportunities Translate data insights into actionable strategies Support deployment of analytics solutions<br><br>Requirements:<br><br>Master’s or PhD in Data Science, AI, or related field10–13+ years in advanced analytics Strong programming (Python, AI/ML frameworks)

Role Overview:<br><br>Drive advanced analytics, predictive modeling, and machine learning initiatives to support business and operational decisions.<br><br>Key Responsibilities:<br><br>Develop predictive and statistical models Identify trends, anomalies, and optimization opportunities Translate data insights into actionable strategies Support deployment of analytics solutions<br><br>Requirements:<br><br>Master’s or PhD in Data Science, AI, or related field10–13+ years in advanced analytics Strong programming (Python, AI/ML frameworks)

<p>We Are Our AI &amp; Data team helps clients transform business challenges into opportunities through advanced analytics, AI, and intelligent decision-making. We work across industries to design and deliver practical analytical solutions. The Work As an AI Decision Science Consultant, you will work with clients to develop analytical solutions, generate insights, and support AI-driven transformation initiatives. Conducting data analysis and statistical modeling Building predictive and analytical solutions Supporting machine learning use cases and AI initiatives Creating dashboards, reports, and decision-support tools Gathering and documenting client requirements Presenting findings and recommendations to stakeholders Collaborating with multidisciplinary consulting teams</p><p><strong>Desired Candidate Profile</strong></p><ul><li>Bachelor's degree in Data Science, Statistics, Mathematics, Engineering, Economics, or related field</li><li>3+ years of analytics, AI, or data science experience</li><li>Strong analytical and problem-solving skills</li><li>Experience with SQL, Python, or similar analytical tools</li><li>Excellent communication and presentation skills</li><li>Bonus Points If You Have Machine learning project experience Data visualization expertise Experience in consulting or client-facing environments</li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>We are looking for a talented and motivated Production Engineer.</p><p>&nbsp;</p><p>In this role, you will be responsible for planning, coordinating, and optimizing manufacturing operations to ensure production targets are achieved safely, efficiently, and to the highest quality standards. You will work closely with cross-functional teams, including Quality, Maintenance, Engineering, to improve production processes, resolve operational challenges, adherence to safety protocols and efficient utilization of resources, and achieve strict deadlines.</p> </div><h2 class="h5">Skills</h2> <div data-jb-field="skills"><p><b>Requirements:</b></p><p>✔ &nbsp;&nbsp;&nbsp;Bachelor's Degree in Mechanical Engineering</p><p>✔ &nbsp;&nbsp;&nbsp;Minimum 3 years of experience in a production/manufacturing environment</p><p>✔ &nbsp;&nbsp;&nbsp;Strong knowledge of production planning, process optimization, and quality control</p><p>✔ &nbsp;&nbsp;&nbsp;Ability to lead shop-floor operations and drive continuous improvement</p><p>✔ &nbsp;&nbsp;&nbsp;Excellent problem-solving and communication skills</p><p>✔ &nbsp;&nbsp;&nbsp;Hands-on experience with Lathe and CNC machine operations</p><p>✔ &nbsp;&nbsp;&nbsp;Knowledge of machine manufacturing</p></div>

Job Location:<br><br>Al Najada Doha Hotel By Tivoli<br><br>Overview<br><br>Minor Hotels is an international hotel owner, operator and investor, currently with a diverse portfolio of over 530 properties designed intelligently to appeal to a variety of travellers, serving new passions as well as personal needs. Through our Anantara, Avani, Elewana, Oaks, NH Hotels, NH Collection, nhow and TIVOLI properties, Minor Hotels operates in 50+ countries across Asia Pacific, the Middle East, Africa, the Indian Ocean, Europe and South America.<br><br>The Housekeeping Supervisor assists the Executive Housekeeper and Assistant Executive Housekeeper in ensuring the smooth operation of the department. The Supervisor needs to assign the team's daily duties and inspect work for adherence to prescribed standards of cleanliness. You will oversee the development of your team to ensure delivery of exceptional customer experiences.<br><br>Qualifications<br><br>Experience in a supervisory role within a Hotel and collaborating with business stakeholders Have the ability to adapt to shifting priorities and align activities to meet organizational goals Strong presentation skills and organisational skills High degree of self-awareness with demonstrated aptitude for self-improvement<br><br>Not the right fit? Set up email alerts as new job postings become available that meet your interest!

About the Role We are looking for an experienced Senior AI Engineer who can develop AI systems and tools. In this role, you will bridge the gap between artificial intelligence and robust software engineering by building the backend infrastructure that brings our AI solutions to life in production. What You'll DoDesign, develop, and deploy scalable AI systems and internal tools. Architect, build, and maintain the backend systems required to support complex AI operations. Integrate machine learning models into secure, production-ready environments. Ensure the performance, reliability, and scalability of AI-driven applications and APIs. What We're Looking For Proven experience working as a Senior AI Engineer, Machine Learning Engineer, or Backend Software Engineer. Strong backend development skills and a deep understanding of software engineering principles. Hands-on experience building, scaling, and deploying AI tools and systems. Solid understanding of API design, cloud infrastructure, and database management.

Mandatory Requirement: This role is strictly limited to candidates from EdTech backgrounds with proven AI application experience in learning or education platforms<br>Antal is partnering with a multinational conglomerate operating across Central America and other regions to establish a national EdTech transformation division in Qatar.<br>This initiative is a large-scale, AI-enabled education modernization program designed to support the evolution of Qatar’s education ecosystem through integrated curriculum transformation, certification alignment, teacher enablement, and a unified AI-powered learning platform.<br>The program is being developed in close collaboration with:Ministry-level stakeholders Global curriculum and certification partners A founding advisory group of education and technology experts<br>Job Title - Founding Managing Director / Program COOCompensation - $12,000 to $15,000 + Benefits + Bonus<br>Role Overview We are seeking a Founding Managing Director / Program COO to lead the transformation of a national AI-enabled education initiative from concept to pilot and ultimately to large-scale deployment. This role is responsible for converting a strategic vision into a structured, executable, and scalable operating system spanning curriculum integration, teacher enablement, certification alignment, and AI-enabled learning infrastructure. This is a true builder-operator role, not a traditional program management position. The individual will act as the central execution leader across technology, curriculum, partners, governance, and institutional stakeholders.<br>Mandate The Program COO will serve as the operational backbone of the initiative, responsible for building and running the entire execution ecosystem, including partners, pilots, delivery systems, and governance structures. They will coordinate across:Chief AI / Systems Architect Curriculum and certification partners Technology and platform vendors Teacher enablement teams Government / Ministry and institutional stakeholders Pilot schools and deployment teams<br>Core Responsibilities1. End-to-End Implementation Architecture2. Partner & Ecosystem Orchestration3. Teacher Intelligence Lab Buildout4. Pilot Deployment Execution5. Platform & Technology Coordination6. Government & Institutional Readiness7. Operating Model & Team Buildout8. Governance & Execution Discipline<br>Ideal Candidate Profile The ideal candidate is a technology-driven education transformation leader with strong execution depth.<br>Must-have experience:Top-tier academic background (IIT / IIM / IISc / NIT or equivalent) preferred12–20+ years in:EdTech / digital learning platforms AI-enabled education systems Enterprise learning / corporate academies Large-scale digital transformation programs Experience working with major global technology or consulting ecosystems (e.g., Microsoft, Google, IBM, Accenture, TCS, Infosys, Wipro, Samsung or similar) Proven ability to lead multi-stream, multi-stakeholder programs at scale Strong exposure to K–12 education systems or teacher enablement platforms<br>Core capabilities:Strong understanding of AI applications in learning ecosystems Ability to translate strategy into execution systems Experience building operating models from scratch Strong stakeholder management (government, enterprise, institutional) High execution discipline (PMP / SAFe or equivalent exposure preferred) Comfortable operating in ambiguity and early-stage environments AI-fluent in day-to-day workflows<br>Leadership Traits Highly structured and execution-oriented Strong systems thinker Calm under pressure Strong communicator across technical and non-technical audiences Entrepreneurial mindset Comfortable building while operating Long-term potential to evolve into Group COO<br>Not a Fit IfPure academic with no delivery experience Theoretical AI researcher without implementation exposure Traditional school administrator without tech depth Junior program/project manager Consultant focused on documentation over execution Operator of existing systems without prior zero-to-one builds<br>First 90-Day Outcomes The candidate should be capable of delivering:End-to-end implementation roadmap Partner dependency and integration matrix Teacher Intelligence Lab operating model Pilot deployment blueprint Initial organization structure and hiring plan Technology and infrastructure coordination plan Ministry-ready execution deck Budget and resource plan for pilot phase Governance and reporting framework Risk and mitigation register

Job Description<br><br>Must Have<br><br> 6–10 years of experience in data science, analytics, or applied statistics, including a demonstrable track record of leading projects end to end. Senior technical voice on a data science team — setting modeling standards, reviewing peer work, and mentoring less-experienced data scientists. Deep command of statistics, experimental design, and a broad modeling toolkit spanning classical machine learning, time-series, and deep learning. Demonstrated ability to translate ambiguous business and policy questions into rigorous, decision-ready analysis for executive audiences. Commitment to statistical soundness, reproducibility, and continuous learning in statistical and machine-learning methods. <br><br>Nice to have<br><br> Experience in the government or large-enterprise sector, ideally in Qatar or the wider GCC. Familiarity with Oracle Cloud Infrastructure (OCI) and cloud-based analytics environments. Exposure to deploying models into production in partnership with engineering teams. Domain expertise in a relevant vertical such as public sector, finance, telecom, or healthcare. Experience with causal inference or advanced experimentation methods. Working knowledge of data visualization or business-intelligence tools for stakeholder communication. Relevant data science or cloud certifications. <br><br>Responsibilities<br><br> Lead the design and execution of advanced analytics and statistical modeling projects, from problem framing through to validated, decision-ready insight. Translate ambiguous business and policy questions into well-defined data science problems, measurable hypotheses, and analytical plans. Define and enforce modeling methodology, experimentation standards (including A/B testing and quasi-experimental designs), and model validation practices across the team. Build, evaluate, and interpret advanced predictive and statistical models using Python (pandas, scikit-learn, statsmodels) and SQL. Select appropriate techniques across regression, classification, clustering, time-series, deep learning, and causal inference, and justify trade-offs to stakeholders. Own the statistical soundness of analytical deliverables, including assumptions, uncertainty quantification, and limitations. Establish reproducible analytical workflows and promote good practice in code quality, documentation, and version control within the team. Present findings and recommendations to senior, often non-technical, stakeholders through clear narratives and visualizations that drive decisions. Review and provide technical feedback on the analytical work of data scientists, raising the overall standard of the team. Mentor and coach junior and mid-level data scientists, supporting their technical and professional growth. Partner with machine-learning and AI engineers to hand off validated models for productionization and to define monitoring and success metrics. Contribute to proposals, scoping, and effort estimation for new data science engagements. <br><br>Qualifications<br><br> Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field; Master's or PhD preferred. Deep proficiency in Python for analysis and the scientific stack (pandas, Num Py, scikit-learn, statsmodels) and strong SQL. Strong foundation in statistics and experimental design, with command of a broad range of modeling techniques. Hands-on experience applying deep learning and neural network architectures using frameworks such as Tensor Flow or PyTorch. Experience designing and interpreting experiments and translating results into business recommendations. Demonstrated ability to frame business problems and communicate analytical results to executive and non-technical audiences. Experience mentoring analysts or data scientists and setting analytical standards or methodology. Strong understanding of the end-to-end data science lifecycle, including data quality, validation, and model handoff. Ability to manage multiple workstreams and stakeholders simultaneously.

Job Description<br><br>Must Have<br><br> 6–10 years of experience in data science, analytics, or applied statistics, including a demonstrable track record of leading projects end to end. Senior technical voice on a data science team — setting modeling standards, reviewing peer work, and mentoring less-experienced data scientists. Deep command of statistics, experimental design, and a broad modeling toolkit spanning classical machine learning, time-series, and deep learning. Demonstrated ability to translate ambiguous business and policy questions into rigorous, decision-ready analysis for executive audiences. Commitment to statistical soundness, reproducibility, and continuous learning in statistical and machine-learning methods. <br><br>Nice to have<br><br> Experience in the government or large-enterprise sector, ideally in Qatar or the wider GCC. Familiarity with Oracle Cloud Infrastructure (OCI) and cloud-based analytics environments. Exposure to deploying models into production in partnership with engineering teams. Domain expertise in a relevant vertical such as public sector, finance, telecom, or healthcare. Experience with causal inference or advanced experimentation methods. Working knowledge of data visualization or business-intelligence tools for stakeholder communication. Relevant data science or cloud certifications. <br><br>Responsibilities<br><br> Lead the design and execution of advanced analytics and statistical modeling projects, from problem framing through to validated, decision-ready insight. Translate ambiguous business and policy questions into well-defined data science problems, measurable hypotheses, and analytical plans. Define and enforce modeling methodology, experimentation standards (including A/B testing and quasi-experimental designs), and model validation practices across the team. Build, evaluate, and interpret advanced predictive and statistical models using Python (pandas, scikit-learn, statsmodels) and SQL. Select appropriate techniques across regression, classification, clustering, time-series, deep learning, and causal inference, and justify trade-offs to stakeholders. Own the statistical soundness of analytical deliverables, including assumptions, uncertainty quantification, and limitations. Establish reproducible analytical workflows and promote good practice in code quality, documentation, and version control within the team. Present findings and recommendations to senior, often non-technical, stakeholders through clear narratives and visualizations that drive decisions. Review and provide technical feedback on the analytical work of data scientists, raising the overall standard of the team. Mentor and coach junior and mid-level data scientists, supporting their technical and professional growth. Partner with machine-learning and AI engineers to hand off validated models for productionization and to define monitoring and success metrics. Contribute to proposals, scoping, and effort estimation for new data science engagements. <br><br>Qualifications<br><br> Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field; Master's or PhD preferred. Deep proficiency in Python for analysis and the scientific stack (pandas, Num Py, scikit-learn, statsmodels) and strong SQL. Strong foundation in statistics and experimental design, with command of a broad range of modeling techniques. Hands-on experience applying deep learning and neural network architectures using frameworks such as Tensor Flow or PyTorch. Experience designing and interpreting experiments and translating results into business recommendations. Demonstrated ability to frame business problems and communicate analytical results to executive and non-technical audiences. Experience mentoring analysts or data scientists and setting analytical standards or methodology. Strong understanding of the end-to-end data science lifecycle, including data quality, validation, and model handoff. Ability to manage multiple workstreams and stakeholders simultaneously.

Job Description<br><br>Must Have<br><br> 6–10 years of experience in data science, analytics, or applied statistics, including a demonstrable track record of leading projects end to end. Senior technical voice on a data science team — setting modeling standards, reviewing peer work, and mentoring less-experienced data scientists. Deep command of statistics, experimental design, and a broad modeling toolkit spanning classical machine learning, time-series, and deep learning. Demonstrated ability to translate ambiguous business and policy questions into rigorous, decision-ready analysis for executive audiences. Commitment to statistical soundness, reproducibility, and continuous learning in statistical and machine-learning methods. <br><br>Nice to have<br><br> Experience in the government or large-enterprise sector, ideally in Qatar or the wider GCC. Familiarity with Oracle Cloud Infrastructure (OCI) and cloud-based analytics environments. Exposure to deploying models into production in partnership with engineering teams. Domain expertise in a relevant vertical such as public sector, finance, telecom, or healthcare. Experience with causal inference or advanced experimentation methods. Working knowledge of data visualization or business-intelligence tools for stakeholder communication. Relevant data science or cloud certifications. <br><br>Responsibilities<br><br> Lead the design and execution of advanced analytics and statistical modeling projects, from problem framing through to validated, decision-ready insight. Translate ambiguous business and policy questions into well-defined data science problems, measurable hypotheses, and analytical plans. Define and enforce modeling methodology, experimentation standards (including A/B testing and quasi-experimental designs), and model validation practices across the team. Build, evaluate, and interpret advanced predictive and statistical models using Python (pandas, scikit-learn, statsmodels) and SQL. Select appropriate techniques across regression, classification, clustering, time-series, deep learning, and causal inference, and justify trade-offs to stakeholders. Own the statistical soundness of analytical deliverables, including assumptions, uncertainty quantification, and limitations. Establish reproducible analytical workflows and promote good practice in code quality, documentation, and version control within the team. Present findings and recommendations to senior, often non-technical, stakeholders through clear narratives and visualizations that drive decisions. Review and provide technical feedback on the analytical work of data scientists, raising the overall standard of the team. Mentor and coach junior and mid-level data scientists, supporting their technical and professional growth. Partner with machine-learning and AI engineers to hand off validated models for productionization and to define monitoring and success metrics. Contribute to proposals, scoping, and effort estimation for new data science engagements. <br><br>Qualifications<br><br> Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field; Master's or PhD preferred. Deep proficiency in Python for analysis and the scientific stack (pandas, Num Py, scikit-learn, statsmodels) and strong SQL. Strong foundation in statistics and experimental design, with command of a broad range of modeling techniques. Hands-on experience applying deep learning and neural network architectures using frameworks such as Tensor Flow or PyTorch. Experience designing and interpreting experiments and translating results into business recommendations. Demonstrated ability to frame business problems and communicate analytical results to executive and non-technical audiences. Experience mentoring analysts or data scientists and setting analytical standards or methodology. Strong understanding of the end-to-end data science lifecycle, including data quality, validation, and model handoff. Ability to manage multiple workstreams and stakeholders simultaneously.

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Drive advanced analytics, predictive modeling, and machine learning initiatives to support business and operational decisions.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><h2>Requirements</h2><ul><li>Master s or PhD in Data Science, AI, or related field</li><li>10 13+ years in advanced analytics</li><li>Strong programming (Python, AI/ML frameworks)</li></ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Job Summary <br> <p>The Associate, Data Science plays a foundational role in supporting data science initiatives across the bank. The role involves working under the guidance of senior team members to build and deploy machine learning models, conduct exploratory data analysis, and generate data-driven insights to solve business problems. The associate collaborates with business units to understand requirements, supports model development, and contributes to building scalable data science assets that align with QNB’s strategic goals.</p><br> <br> <br><br> Main Responsibilities <br> <p>A. Shareholder &amp; Financial: - Support the development and tracking of KPIs to measure impact of data science initiatives. - Assist in delivering data analytics solutions that drive business efficiency and revenue growth. - Take part in the overall QNB Data &amp; Analytics strategy execution. - Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Act within the limits of the powers delegated to the incumbent. </p><br><p>B. Customer (Internal &amp; External): - Work with internal stakeholders to understand business needs and translate them into data problems. - Assist in preparing clear, concise, and insightful reports or dashboards for business users. - Support model testing and deployment activities, ensuring stakeholder alignment and timely delivery. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - Build and maintain strong/effective relationships with related departments/units to achieve the Group’s objectives. - Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. </p><br><p>C. Internal (Processes, Products, Regulatory): - Support the AVP and other senior data scientists in developing machine learning and statistical models. - Prepare and clean large datasets for analysis and modelling purposes. - Contribute to the implementation of AI/ML pipelines and production-ready solutions. - Document methodologies, outcomes, and learnings for reproducibility and scaling. - Develop predictive models using a variety of advanced machine learning techniques to extract meaningful insights. - Research and implement cutting-edge techniques and tools in data analytics and artificial intelligence to streamline data analysis processes and enhance decision-making. - Identify and implement new statistical or mathematical methodologies as required for specific data-driven projects. - Build robust data-driven models to address complex business questions and employ large-scale experimentation, analysis, and visualization techniques to generate efficient and repeatable insights. </p><br><p>D. Learning &amp; Knowledge: - Stay updated on the latest trends in machine learning, AI, and analytics tools. - Participate in training programs and learning sessions to build advanced analytics capability. - Proactively seek feedback and mentorship from senior team members. - Seek out opportunities to stay current with advancements in data analytics fields. - Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects.</p><br> <br> <br><br> Education and Experience Requirements <br> <p>- Bachler Degree University in data science, Computer Science, Mathematics, Engineering, or a related field. </p><br><p>- Familiarity with machine learning techniques, data wrangling, and model evaluation practices. </p><br><p>- High Level knowledge in data science tools like Python, R and Jupiter notebooks is desirable.</p><br> <br> <br> </div>

Additional Information<br><br>Job Number 26103480<br><br>Job Category Housekeeping & Laundry<br><br>Location Building No. 153 Street No. 347, Lusail, Qatar, Qatar,VIEW ON MAP<br><br>Schedule Full Time<br><br>Located Remotely? N<br><br>Position Type Non-Management<br><br>Utiliser et contrôler les machines à laver, de nettoyage à sec et les sèche-linge, faire l'appoint de produits lavant et nettoyer les filtres au besoin. Isoler les articles tachés ou endommagés et déterminer s'il convient de les réparer, de les détacher, de les relaver ou de les jeter. Contrôler la propreté des articles qui sortent des machines à laver, sèche-linge ou machines de nettoyage à sec et les placer dans les chariots de linge propre. Régler la durée et la température de séchage des sèche-linge en fonction des tissus/textiles. Retirer les peluches et autres éléments des filtres des sèche-linge et des machines de nettoyage à sec et vider les filtres après chaque chargement. Plier les articles propres à la taille indiquée, à la main ou à l'aide d'une machine. Tenir à jour la liste des articles nettoyés.<br><br>Suivre et appliquer toutes les politiques et procédures de sécurité de la chaîne; rapporter les problèmes de maintenance, les risques d’accident, les accidents ou les blessures; suivre les formations et obtenir les certifications requises en matière de sécurité. Veiller à ce que son uniforme et son apparence soient propres et professionnels. Respecter la confidentialité des renseignements exclusifs; protéger les biens de l’entreprise. Soutenir tous les collègues et les traiter avec dignité et respect. Soutenir l’équipe dans l’atteinte des objectifs communs. Se conformer aux attentes et aux normes d’assurance qualité. Déplacer, soulever, porter, pousser, tirer et placer des objets pesant jusqu’à 25 livres (11,3 kg) sans assistance. Se tenir debout, assis ou marcher pendant une période prolongée ou pour un quart de travail complet. Inspecter visuellement les outils, l’équipement et les machines (p. ex., pour identifier les défauts). Atteindre les objets au-dessus de la tête et au-dessous des genoux, y compris se plier, faire des rotations du corps, tirer et se baisser. Se déplacer dans des espaces étroits, confinés, ou élevés. Se déplacer sur des surfaces en pente, inégales ou des marches glissantes. Monter et descendre les escaliers et les rampes de service. Effectuer toutes les autres tâches demandées par les responsables et qui correspondent au poste.<br><br>Qualifications Recommandées<br><br>Niveau d’études:Aucun diplôme d’études secondaires ou équivalence de niveau secondaire<br><br>Expérience de travail connexe:Aucune expérience de travail connexe.<br><br>Expérience de supervision:Aucune expérience de supervision.<br><br>Permis ou certification:Aucune<br><br>Chez Marriott International, nous nous engageons à promouvoir l’égalité d’accès à l’emploi, à accueillir dignement chaque personne et à offrir les mêmes opportunités à tous. Nous avons instauré un environnement dans lequel les particularités de nos collaborateurs sont appréciées et célébrées. Notre plus grande force réside dans le mélange varié de cultures, de compétences et d’expériences de nos collaborateurs. Nous veillons à prévenir toute discrimination fondée sur des critères protégés, notamment le handicap, le statut de vétéran et tout autre aspect couvert par la loi en vigueur.<br><br>Le Méridien puise son inspiration dans l'époque des voyages glamour, célébrant chaque culture par le prisme d'un esprit épicurien résolument européen. Notre clientèle est curieuse et créative. Cosmopolite et avide de culture, elle apprécie les échanges et elle aime ralentir le rythme pour savourer pleinement l'endroit où elle se trouve. Nous offrons un service à la fois chic et authentique, vraiment inoubliable grâce à des expériences qui incitent à profiter des plus beaux moments de la vie. Nous recherchons des personnes curieuses et créatives pour rejoindre notre équipe. Si vous aimez nouer des liens avec des clients partageant le même état d'esprit et avez à cœur de créer des expériences inoubliables, nous vous invitons à découvrir les offres d'emploi chez Le Méridien. En rejoignant Le Méridien, vous intégrerez le portefeuille d'enseignes de Marriott International. Rejoignez une entreprise qui vous donne la possibilité de donner le meilleur de vous-même, de trouver un sens à votre vie professionnelle, de faire partie d'une équipe internationale d'exception et de devenir la meilleure version de vous-même.

Overview<br><br>University of Doha for Science and Technology (UDST), officially established by Emiri Decision No. 13 of 2022, is Qatar’s first national applied university and the country’s premier destination for academic, technical, and professional education. With more than 9,000 students and 700 staff, UDST offers over 70 bachelor’s, master’s, diploma, and certificate programs across its five colleges: Business, Computing & Information Technology, Engineering & Technology, Health Sciences, and General Education. In addition, UDST houses specialized training centers that serve both individuals and industry<br><br>UDST is recognized for its student-centered learning, cutting-edge facilities, and applied, experiential approach. Our world-class faculty and researchers leverage innovative learning technologies and foster partnerships with global institutions to develop highly skilled graduates who contribute directly to Qatar’s knowledge-based economy and support the goals of Qatar National Vision 2030. As a growing hub for research and innovation, UDST is home to advanced projects that bridge academia and industry.<br><br>UDST Center of Excellence - Artificial Intelligence and Innovation is dedicated to advancing cutting-edge AI research and developing practical solutions that tackles real-world challenges. Our mission is to drive scientific progress and technological innovation in intelligent systems, contributing to Qatar's transition to a knowledge-based economy in line with Qatar National Vision 2030.<br><br>We are seeking an outstanding Postdoctoral Researcher to join our team at the Center of Excellence in Artificial Intelligence and Innovation. This role focuses on conducting applied research in machine learning, federated learning, and explainable AI (XAI) with real-world applications in healthcare, energy, and smart infrastructure. You will develop privacy-preserving machine learning systems, create interpretable AI solutions, and deploy models on edge and cloud platforms. This is an excellent opportunity to advance trustworthy AI research while contributing to Qatar’s innovation priorities and digital transformation.<br><br>Responsibilities<br><br>Key Responsibilities<br><br>Conduct applied research in machine learning, federated learning, and explainable AI across domains such as healthcare, energy, and smart infrastructure Develop privacy-preserving machine learning systems and interpretable AI solutions that ensure transparency and trust Deploy machine learning models on edge and cloud platforms, ensuring robustness and scalability Publish research findings in top-tier peer-reviewed conferences and journals Lead and contribute to high-impact research projects aligned with the Center's priorities Ensure reproducibility and documentation of research through best practices in code and data management Integrate XAI techniques to ensure AI solutions meet ethical standards and domain-specific requirements Collaborate with internal and external stakeholders on interdisciplinary research initiatives Contribute to research proposals and external funding applications to support the Center's growth Mentor junior researchers, graduate students, and research assistants<br><br>Qualifications<br><br>Required Qualifications<br><br>PhD in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field Demonstrated research experience in machine learning, with focus on federated learning, explainable AI, or privacy-preserving MLStrong publication record in peer-reviewed journals and top-tier AI/ML conferences (e.g., Neur IPS, ICML, ICLR, AAAI, CVPR, KDD) Expertise in deep learning frameworks (PyTorch, Tensor Flow, Keras) and classical ML tools (scikit-learn, XGBoost) Strong background in machine learning, federated learning, or explainable AIExperience with evaluating AI models, benchmark design, and assessment methodologies Experience with explainable AI libraries (e.g., SHAP, LIME, Captum) and interpretability techniques Experience with federated learning frameworks (e.g., Flower, Tensor Flow Federated) or privacy-preserving MLProven ability to conduct independent research and contribute to collaborative research teams Excellent analytical, problem-solving, and communication skills, including research presentations and technical writing Proficiency with version control systems (Git) and reproducible research practices Experience with computational resources and high-performance computing environments Fluency in written and spoken English<br><br>Preferred Qualifications How to Apply<br><br>Experience applying ML to healthcare, energy, or smart infrastructure domains Familiarity with AI safety, alignment, fairness, bias detection, or responsible AI research Experience with cloud and edge deployment platforms (e.g., AWS Sage Maker, Azure ML, Docker, Kubernetes) Knowledge of MLOps practices, CI/CD pipelines, and model deployment Experience with model monitoring, drift detection, and retraining strategies Experience with data engineering and preprocessing tools (e.g., Spark, Airflow, data versioning) Understanding of human-AI interaction and user-centered AI design Familiarity with domain-specific toolkits (e.g., MONAI for medical imaging, FHIR for healthcare data) Track record of research impact (citations, h-index, awards) Experience with interdisciplinary research or industry collaborations Previous postdoctoral or industrial research experience Experience with grant writing and research funding applications Contributions to open-source AI projects or frameworks Arabic language skills What We Offer Competitive salary and comprehensive benefits package Opportunity to conduct applied research in ML, federated learning, and explainable AI with real-world impact in healthcare and energy Collaborative and dynamic work environment with cutting-edge technology Access to state-of-the-art facilities and computational resources through strategic partnerships Professional development opportunities, international collaborations, and conference participation<br>Interested Candidates Should Submit The Following Documents<br><br>Updated CV/Resume Cover letter highlighting research experience, interests, and motivation List of publications and research statement (required) Contact information for two professional references<br><br>Application Deadline: 31st March 2026<br><br>UDST is an equal opportunity employer committed to building a diverse and inclusive workforce. We welcome applications from all qualified candidates regardless of race, color, religion, gender, national origin, age, disability, or veteran status.

Overview<br><br>University of Doha for Science and Technology (UDST), officially established by Emiri Decision No. 13 of 2022, is Qatar’s first national applied university and the country’s premier destination for academic, technical, and professional education. With more than 9,000 students and 700 staff, UDST offers over 70 bachelor’s, master’s, diploma, and certificate programs across its five colleges: Business, Computing & Information Technology, Engineering & Technology, Health Sciences, and General Education. In addition, UDST houses specialized training centers that serve both individuals and industry<br><br>UDST is recognized for its student-centered learning, cutting-edge facilities, and applied, experiential approach. Our world-class faculty and researchers leverage innovative learning technologies and foster partnerships with global institutions to develop highly skilled graduates who contribute directly to Qatar’s knowledge-based economy and support the goals of Qatar National Vision 2030. As a growing hub for research and innovation, UDST is home to advanced projects that bridge academia and industry.<br><br>UDST Center of Excellence - Artificial Intelligence and Innovation is dedicated to advancing cutting-edge AI research and developing practical solutions that tackles real-world challenges. Our mission is to drive scientific progress and technological innovation in intelligent systems, contributing to Qatar's transition to a knowledge-based economy in line with Qatar National Vision 2030.<br><br>We are seeking an outstanding Postdoctoral Researcher to join our team at the Center of Excellence in Artificial Intelligence and Innovation. This role focuses on conducting applied research in machine learning, federated learning, and explainable AI (XAI) with real-world applications in healthcare, energy, and smart infrastructure. You will develop privacy-preserving machine learning systems, create interpretable AI solutions, and deploy models on edge and cloud platforms. This is an excellent opportunity to advance trustworthy AI research while contributing to Qatar’s innovation priorities and digital transformation.<br><br>Responsibilities<br><br>Key Responsibilities<br><br>Conduct applied research in machine learning, federated learning, and explainable AI across domains such as healthcare, energy, and smart infrastructure Develop privacy-preserving machine learning systems and interpretable AI solutions that ensure transparency and trust Deploy machine learning models on edge and cloud platforms, ensuring robustness and scalability Publish research findings in top-tier peer-reviewed conferences and journals Lead and contribute to high-impact research projects aligned with the Center's priorities Ensure reproducibility and documentation of research through best practices in code and data management Integrate XAI techniques to ensure AI solutions meet ethical standards and domain-specific requirements Collaborate with internal and external stakeholders on interdisciplinary research initiatives Contribute to research proposals and external funding applications to support the Center's growth Mentor junior researchers, graduate students, and research assistants<br><br>Qualifications<br><br>Required Qualifications<br><br>PhD in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field Demonstrated research experience in machine learning, with focus on federated learning, explainable AI, or privacy-preserving MLStrong publication record in peer-reviewed journals and top-tier AI/ML conferences (e.g., Neur IPS, ICML, ICLR, AAAI, CVPR, KDD) Expertise in deep learning frameworks (PyTorch, Tensor Flow, Keras) and classical ML tools (scikit-learn, XGBoost) Strong background in machine learning, federated learning, or explainable AIExperience with evaluating AI models, benchmark design, and assessment methodologies Experience with explainable AI libraries (e.g., SHAP, LIME, Captum) and interpretability techniques Experience with federated learning frameworks (e.g., Flower, Tensor Flow Federated) or privacy-preserving MLProven ability to conduct independent research and contribute to collaborative research teams Excellent analytical, problem-solving, and communication skills, including research presentations and technical writing Proficiency with version control systems (Git) and reproducible research practices Experience with computational resources and high-performance computing environments Fluency in written and spoken English<br><br>Preferred Qualifications How to Apply<br><br>Experience applying ML to healthcare, energy, or smart infrastructure domains Familiarity with AI safety, alignment, fairness, bias detection, or responsible AI research Experience with cloud and edge deployment platforms (e.g., AWS Sage Maker, Azure ML, Docker, Kubernetes) Knowledge of MLOps practices, CI/CD pipelines, and model deployment Experience with model monitoring, drift detection, and retraining strategies Experience with data engineering and preprocessing tools (e.g., Spark, Airflow, data versioning) Understanding of human-AI interaction and user-centered AI design Familiarity with domain-specific toolkits (e.g., MONAI for medical imaging, FHIR for healthcare data) Track record of research impact (citations, h-index, awards) Experience with interdisciplinary research or industry collaborations Previous postdoctoral or industrial research experience Experience with grant writing and research funding applications Contributions to open-source AI projects or frameworks Arabic language skills What We Offer Competitive salary and comprehensive benefits package Opportunity to conduct applied research in ML, federated learning, and explainable AI with real-world impact in healthcare and energy Collaborative and dynamic work environment with cutting-edge technology Access to state-of-the-art facilities and computational resources through strategic partnerships Professional development opportunities, international collaborations, and conference participation<br>Interested Candidates Should Submit The Following Documents<br><br>Updated CV/Resume Cover letter highlighting research experience, interests, and motivation List of publications and research statement (required) Contact information for two professional references<br><br>Application Deadline: 31st March 2026<br><br>UDST is an equal opportunity employer committed to building a diverse and inclusive workforce. We welcome applications from all qualified candidates regardless of race, color, religion, gender, national origin, age, disability, or veteran status.