Machine operator Jobs

Hiring: AI Engineer (United Arab Emirates) We are currently seeking an innovative and highly motivated AI Engineer to join our growing technology team in the United Arab Emirates. Position:AI Engineer Location:United Arab Emirates Job Type:Full-Time On-site / Hybrid Available Responsibilities:Design, develop, and deploy Artificial Intelligence and Machine Learning solutions Build and optimize Generative AI, Large Language Model (LLM), and Natural Language Processing (NLP) applications Develop intelligent automation systems and AI-powered products Train, fine-tune, evaluate, and monitor machine learning models Collaborate with software engineers, data scientists, and product teams to deliver AI-driven solutions Implement MLOps pipelines for model deployment, monitoring, and lifecycle management Research emerging AI technologies and contribute to innovation initiatives Ensure AI solutions are scalable, secure, and aligned with business objectives Requirements:Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field Strong proficiency in Python and machine learning concepts Experience with Tensor Flow, PyTorch, Scikit-learn, Lang Chain, or similar AI frameworks Knowledge of LLMs, Generative AI, NLP, prompt engineering, and vector databases Experience with cloud platforms such as AWS, Azure, or Google Cloud Familiarity with Docker, Kubernetes, APIs, and MLOps practices Strong analytical, problem-solving, and communication skills Benefits:Competitive salary package Performance-based bonuses Health and insurance benefits Professional development and AI certification support Exposure to cutting-edge AI technologies and regional innovation projects Career advancement opportunities Collaborative and innovation-driven work environment How to Apply:Please send your CV/Resume and a brief self-introduction to our recruitment team. Join us and help build next-generation AI solutions that drive digital transformation, automation, and business innovation across the region!

Home Applied AI Solutions Industry Aligned Upskilling Skills Boost AiMinds Courses Data Analytics Machine Learning Deep Learning Coding Design Research Clean Technology Advanced Manufacturing IoT, 5G & Cybersecurity Business Intelligence Fin Tech Health Tech AgTech<br><br>Home Applied AI Solutions Industry Aligned Upskilling Skills Boost AiMinds Courses Data Analytics Machine Learning Deep Learning Coding Design Research Clean Technology Advanced Manufacturing IoT, 5G & Cybersecurity Business Intelligence Fin Tech Health Tech AgTech<br>Customer Segmentation<br><br>Work Integrated Learning Customer Segmentation<br><br>Customer Segmentation<br><br>What is the main goal for this project?<br><br>The goal of this project is to enhance our marketing campaigns through re-evaluating our customer segmentation. We would like to implement cutting edge technology to analyze our customer segmentation, relative to each of our products and services. From the analysis, we hope to gain insights that will enhance our strategy and help us refocus our product/service marketing.<br><br>Improving pricing and risk selection. Identifying trends and potential predictive mitigation strategies. Developing more sophisticated products and pricing models. Submitting recommendations based on the analysis.<br><br>Duties And Responsibilities<br><br>By the end of the project:<br><br>Current industry standard approaches to Data Analysis and Data Visualization techniques. Unsupervised Machine Learning techniques, Clustering Outlier detection and anomaly identification in the data Understanding of variables that affect the accuracy of the model. Identification of areas for future improvement of the model.<br><br>Final Deliverables Should Include<br><br>All source code. A written report explaining the design process and outcomes.<br><br>Skills To Be Developed<br><br>As part of doing this project, interns can expect to be upskilled on below:<br><br>Energy Management systems, Reinforcement learning algorithms like Q-learning. Python, Machine learning.<br><br>About The Project<br><br> 12 Weeks Marketing Virtual Self-Paced<br><br>Register Now<br><br>Register Now<br><br>Our mission is to equip individuals with in-demand STEM skills, foster Research and Development capabilities, and forge connections, opportunities and partnerships with leading businesses in Emerging Technologies such as Data Science, Machine Learning, Artificial Intelligence, and Virtual/Augmented Reality. These skills and research experiences are highly sought after in diverse sectors including Clean Tech, Advanced Manufacturing, Business Intelligence, Finance, and Healthcare.<br><br>Important Links<br><br>Applied AI Solutions Industry Aligned Upskilling Skillsboost AiMinds Courses Research Privacy Policy<br><br>Contact Info<br><br>Greater Chennai, Indiacontact@m2mtechconnect.com<br><br>Copyright © 2026 M2M Tech Designed By AiReach. All Rights Reserved

Job Description<br><br>Supervise the activities undertaken at the VTS Centre with respect to the types of services provided and the team that has the responsibility for conducting the Vessel Traffic Service (VTS) to the satisfaction level of the Competent Authority as well as vessels and other users<br><br>Responsibilities<br><br>Ensuring that the service provided meets the requirements of both the users and the VTS Authority Coordinating the interface between the VTS, allied services and other port facilities and services Ensuring the efficient running of the VTS operation rooms Carrying out an annual assessment of VTS Operators In conjunction with on-the-job training, carrying out revalidation assessments on VTS Operators Ensure that the WMCC - VTS Centre is always adequately manned and that the equipment is maintained in a constant state of readiness Leadership of the VTS team conducting the general day to day management of high volumes of vessels movements Adheres to Safe Work instruction and SOPsAdheres to Near miss and Incident reporting Senyar system Ensure that enough VTS operators are always available on workplace working effectively and all the equipment is functioning properly To supervise a team of VTS operators with the responsibilities of conducting vessel traffic service as per VTS operational procedures manual and Waterways standard Conduct an in-house training on marine related matters as required Conduct on-the-Job training/toolbox talk for VTS Operators Continuously assessing the VTS Operators performance Managing traffic plan <br><br>Qualifications<br><br>Educational and Technical Qualifications:<br><br>Diploma and VTS Certification log with C0103-2 Certificate A qualification in maritime or transport matters, accompanied with relative experience Experience in Maritime Operations and C0103-2 training is required <br><br>Language Skills:<br><br>Ability to effectively communicate, verbally and written in English, in order to be able to report adequately to superiors and to form good relations, negotiates and resolves conflicts with stakeholders Ability to work effectively in a team, including the ability to respond to the needs of team members and provide them with assistance when required Good working knowledge of computers and conversant with computer applications and communication equipment Ability to maintain confidentiality and to work with third parties and retain professional demeanour in confrontational situations Ability to carry out duties effectively and efficiently and according to defined objectives under minimal supervision Ability to monitor the operational and functional integrity of communications equipment, computer and navigational aid Knowledge of maritime regulations and terminology Flounce in English Language <br><br>Years of Experience:<br><br>A minimum of 3 years as a VTS Operator<br><br>Nature of Experience:<br><br>Relevant experience in the region is preferred

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>The Machine Shop Supervisor will be responsible for overseeing all machining operations, ensuring that production activities are carried out safely, efficiently, and in line with company quality standards and project requirements. The role involves supervising machinists, monitoring workflow, maintaining equipment, and ensuring timely delivery of machining tasks.</p><ul><li><p>Supervise and coordinate daily machining operations, including turning, milling, drilling, and other precision machining processes.</p></li><li><p>Ensure all machining work meets required specifications, tolerances, and quality standards.</p></li><li><p>Plan, schedule, and allocate work to machinists to meet project deadlines.</p></li><li><p>Monitor machine utilization, identify bottlenecks, and optimize production efficiency.</p></li><li><p>Oversee the maintenance and calibration of machine shop equipment and tools.</p></li><li><p>Implement and enforce company safety procedures to maintain a safe working environment.</p></li><li><p>Train, mentor, and guide machinists to enhance skills and performance.</p></li><li><p>Collaborate with engineers, project teams, and other departments to ensure machining work aligns with project needs.</p></li><li><p>Maintain accurate records of production, machine hours, material usage, and quality checks.</p></li></ul><p>Troubleshoot operational issues and propose process improvements for productivity and cost efficiency.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li><p>Diploma or technical certification in Mechanical Engineering, Machining, or related field.</p></li><li><p>Minimum of 5 years’ experience in a machine shop, including supervisory experience.</p></li><li><p>Strong knowledge of machining processes, tools, and equipment.</p></li><li><p>Ability to read and interpret engineering drawings and technical specifications.</p></li><li><p>Good understanding of safety regulations and quality standards in machining.</p></li><li><p>Strong leadership, communication, and team management skills.</p></li><li><p>Detail-oriented with problem-solving abilities.</p></li><li><p>Ability to work under pressure and manage multiple priorities.</p></li></ul><p></p></section>

I’m looking for an AI-native co-founder to help scale Model Operator from a developed thesis into a venture studio with real distribution and product discipline.<br>We’re currently very good at: spotting useful AI capabilities early, applying them to slow or expensive workflows, and designing the context, review paths and controls that let more work move faster without mistakes multiplying.<br>I’m adding a co-founder so we can pursue more and bigger bets. I’m looking for someone who considers themselves technical, with a bias towards growth: turning hypotheses into live experiments, building lead magnets, opening partnerships and creating repeatable distribution. You will not need to own the codebase, but you should be able to challenge platform architecture, spot workflows that will constrain scale, query data and deploy digital assets without hand-holding.<br>We’ll both keep building, developing relationships and closing deals. The gap is someone who can drive demand without forcing product quality to compete for the same founder hours. That gives us room to test more bets and pursue larger addressable markets while keeping the shared platform coherent.<br>___<br>What we're building<br>Model Operator is a venture studio for adjacent AI workflow businesses built on one shared operating layer. We are starting with company context and memory management, alongside voice agents.<br>Version 1 is ready, initial sales calls are being booked, and the business is set-up in the UAE and ready to operate. The immediate job is to target the right deals, allocate founder time responsibly and refine a growth plan that tells us which markets deserve deeper investment.<br>The studio depends on finding ideas that are both correct and overlooked, then testing whether they create meaningful operating leverage. That gives us a precise view of where the value sits, who will pay for it and which capabilities belong in the shared platform. Each experiment should strengthen that platform, making the next product faster to launch and easier to scale.<br>___<br>Who we're looking for<br>Early-scale startup experience matters more than corporate experience. You have worked where the product was live, demand was emerging and missing systems had to be built with lean resources. Your decisions affected growth, delivery quality or survival.<br>You have shipped AI products or workflows used by real people. Codex or Claude Code are part of your normal working environment. You probably have an Open Claw or Hermes Agent too and understand tools, memory, evaluations, and failure modes more than the people who just read about these things.<br>You can create demand as well as software. Strong evidence might include testing offers quickly, opening partnerships, building founder-led sales, finding underpriced distribution, running profitable lead magnets, etc.<br>Your network has practical value. Founders, buyers, operators, and partners respond when you contact them because trust already exists. You should also be willing to invest alongside me, although Model Operator does not need your capital immediately.<br>You know what deserves your own hands. You can enter the codebase, inspect a funnel, speak to customers or fix an operational problem. You can also hire specialists, write precise briefs and review outsourced work without losing ownership over the critical thinking.<br>Workslop irritates you. You can identify weak assumptions, generic reasoning, and fabricated details… You remain the human-in-the-loop because you know enough to steer, challenge and refine the system; you rarely just accept AI outputs, and you definitely don’t copy-paste it into chats for colleagues to digest before you have.<br>Intentionality is important. I won’t build with you if you moan about the pursuit: difficult problems, uncertain markets, ambitious experiments and the pressure of making something work. This is not employment approached as a queue of tasks to clear before switching off.<br>We should direct our lives rather than let circumstances decide what happens. Useful work creates impact; impact builds trust; trust opens opportunities that were unavailable before. When one route closes, you find another worthwhile action rather than deciding there is nothing left to do.<br>You tell the truth early. You do not hide doubts, manufacture agreement or soften your actual view because you’re scared or tactical. You are secure enough to disagree, admit uncertainty and change your mind when the evidence changes.<br>You take endurance seriously. You believe in the role of sport/fitness in maintaining the sustainable energy necessary for proper founder performance. You understand burnout prevention starts before exhaustion.<br>What we’d own together<br>Test context management, voice agent and adjacent workflow opportunities Develop repeatable routes to market through offers, sales and partnerships Turn recurring client problems into reusable infrastructure Decide which experiments deserve more capital and which should stop Recruit specialists where necessary Operate at AI-native speed while protecting reliability and trust<br>___<br>Structure<br>This is a co-founder role with equity and vesting.<br>You must be able to contribute at least 20 focused hours each week from the outset, with a credible path towards deeper involvement.<br>Final responsibilities and equity will reflect commitment, demonstrated contribution, existing assets and shared risk.<br>____<br>Apply:<br>Send me:<br>Your early-scale startup experience and proof-of-value. An AI product or workflow you personally shipped. How you use Codex/Claude Code/Open Claw/Hermes Agent. Evidence that you can create distribution or commercial momentum. Your location, availability and eventual investment appetite.<br>Feel free to contact alexander@modeloperator.io<br>Links to products, repos, experiments and commercial results matter more than a polished CV. To be clear though, I do value a quality education.<br>Use AI if it improves the application. Own every sentence you send. I’ll respond to whoever’s not wasting my time.<br><br>Industry Artificial Intelligence<br>Employment Type Part-time

I’m looking for an AI-native co-founder to help scale Model Operator from a developed thesis into a venture studio with real distribution and product discipline.<br>We’re currently very good at: spotting useful AI capabilities early, applying them to slow or expensive workflows, and designing the context, review paths and controls that let more work move faster without mistakes multiplying.<br>I’m adding a co-founder so we can pursue more and bigger bets. I’m looking for someone who considers themselves technical, with a bias towards growth: turning hypotheses into live experiments, building lead magnets, opening partnerships and creating repeatable distribution. You will not need to own the codebase, but you should be able to challenge platform architecture, spot workflows that will constrain scale, query data and deploy digital assets without hand-holding.<br>We’ll both keep building, developing relationships and closing deals. The gap is someone who can drive demand without forcing product quality to compete for the same founder hours. That gives us room to test more bets and pursue larger addressable markets while keeping the shared platform coherent.<br>___<br>What we're building<br>Model Operator is a venture studio for adjacent AI workflow businesses built on one shared operating layer. We are starting with company context and memory management, alongside voice agents.<br>Version 1 is ready, initial sales calls are being booked, and the business is set-up in the UAE and ready to operate. The immediate job is to target the right deals, allocate founder time responsibly and refine a growth plan that tells us which markets deserve deeper investment.<br>The studio depends on finding ideas that are both correct and overlooked, then testing whether they create meaningful operating leverage. That gives us a precise view of where the value sits, who will pay for it and which capabilities belong in the shared platform. Each experiment should strengthen that platform, making the next product faster to launch and easier to scale.<br>___<br>Who we're looking for<br>Early-scale startup experience matters more than corporate experience. You have worked where the product was live, demand was emerging and missing systems had to be built with lean resources. Your decisions affected growth, delivery quality or survival.<br>You have shipped AI products or workflows used by real people. Codex or Claude Code are part of your normal working environment. You probably have an Open Claw or Hermes Agent too and understand tools, memory, evaluations, and failure modes more than the people who just read about these things.<br>You can create demand as well as software. Strong evidence might include testing offers quickly, opening partnerships, building founder-led sales, finding underpriced distribution, running profitable lead magnets, etc.<br>Your network has practical value. Founders, buyers, operators, and partners respond when you contact them because trust already exists. You should also be willing to invest alongside me, although Model Operator does not need your capital immediately.<br>You know what deserves your own hands. You can enter the codebase, inspect a funnel, speak to customers or fix an operational problem. You can also hire specialists, write precise briefs and review outsourced work without losing ownership over the critical thinking.<br>Workslop irritates you. You can identify weak assumptions, generic reasoning, and fabricated details… You remain the human-in-the-loop because you know enough to steer, challenge and refine the system; you rarely just accept AI outputs, and you definitely don’t copy-paste it into chats for colleagues to digest before you have.<br>Intentionality is important. I won’t build with you if you moan about the pursuit: difficult problems, uncertain markets, ambitious experiments and the pressure of making something work. This is not employment approached as a queue of tasks to clear before switching off.<br>We should direct our lives rather than let circumstances decide what happens. Useful work creates impact; impact builds trust; trust opens opportunities that were unavailable before. When one route closes, you find another worthwhile action rather than deciding there is nothing left to do.<br>You tell the truth early. You do not hide doubts, manufacture agreement or soften your actual view because you’re scared or tactical. You are secure enough to disagree, admit uncertainty and change your mind when the evidence changes.<br>You take endurance seriously. You believe in the role of sport/fitness in maintaining the sustainable energy necessary for proper founder performance. You understand burnout prevention starts before exhaustion.<br>What we’d own together<br>Test context management, voice agent and adjacent workflow opportunities Develop repeatable routes to market through offers, sales and partnerships Turn recurring client problems into reusable infrastructure Decide which experiments deserve more capital and which should stop Recruit specialists where necessary Operate at AI-native speed while protecting reliability and trust<br>___<br>Structure<br>This is a co-founder role with equity and vesting.<br>You must be able to contribute at least 20 focused hours each week from the outset, with a credible path towards deeper involvement.<br>Final responsibilities and equity will reflect commitment, demonstrated contribution, existing assets and shared risk.<br>____<br>Apply:<br>Send me:<br>Your early-scale startup experience and proof-of-value. An AI product or workflow you personally shipped. How you use Codex/Claude Code/Open Claw/Hermes Agent. Evidence that you can create distribution or commercial momentum. Your location, availability and eventual investment appetite.<br>Feel free to contact alexander@modeloperator.io<br>Links to products, repos, experiments and commercial results matter more than a polished CV. To be clear though, I do value a quality education.<br>Use AI if it improves the application. Own every sentence you send. I’ll respond to whoever’s not wasting my time.<br><br>Industry Artificial Intelligence<br>Employment Type Part-time

We are seeking an experienced Data Engineer to join a high-performing data and analytics team driving enterprise-wide transformation initiatives. This role offers the opportunity to work with modern cloud-native architectures, large-scale datasets, AI use cases, and advanced data technologies that power analytics, business intelligence, and machine learning solutions.<br>Key Responsibilities Design, develop, and optimize scalable batch and real-time data pipelines. Build and maintain enterprise data lakes, lakehouse architectures, and curated analytical datasets. Develop high-performance SQL and Python code for large-scale data processing workloads. Implement robust data quality, validation, monitoring, and observability frameworks. Develop cloud-native data solutions and infrastructure-as-code deployments. Collaborate closely with Data Scientists, BI teams, and business stakeholders to deliver trusted and governed data products. Support AI and machine learning initiatives by preparing high-quality training datasets and enabling MLOps workflows.<br>Required Experience5+ years of experience in Data Engineering. Strong experience designing and building ETL/ELT pipelines at scale. Advanced expertise in SQL and Python. Hands-on experience with cloud data platforms, preferably Azure. Experience with modern data warehousing and lakehouse architectures. Exposure to CI/CD and infrastructure automation practices.<br>Top Skills for the Ideal Candidate Microsoft Fabric Azure Data Factory (ADF) Databricks PySpark Python Advanced SQLLakehouse Architecture Delta Lake Azure Synapse Analytics Terraform Infrastructure as Code (IaC) Git Hub Actions Azure Dev Ops Data Governance Data Quality Frameworks Change Data Capture (CDC) API Integrations Streaming Data Pipelines MLOps Enablement Metadata Management Data Lineage<br>Nice to Have Scala Hadoop ecosystem exposure Machine Learning pipeline experience Experience supporting enterprise AI initiatives<br>If you enjoy solving complex data challenges and building platforms that enable data-driven decision making at scale, we would love to hear from you.#Data Engineer #Senior Data Engineer #Azure #Microsoft Fabric #Databricks #PySpark #Data Engineering #Machine Learning #AI #Analytics #Cloud Engineering #UAEJobs #Hiring

We are seeking an experienced Data Engineer to join a high-performing data and analytics team driving enterprise-wide transformation initiatives. This role offers the opportunity to work with modern cloud-native architectures, large-scale datasets, AI use cases, and advanced data technologies that power analytics, business intelligence, and machine learning solutions.<br>Key Responsibilities Design, develop, and optimize scalable batch and real-time data pipelines. Build and maintain enterprise data lakes, lakehouse architectures, and curated analytical datasets. Develop high-performance SQL and Python code for large-scale data processing workloads. Implement robust data quality, validation, monitoring, and observability frameworks. Develop cloud-native data solutions and infrastructure-as-code deployments. Collaborate closely with Data Scientists, BI teams, and business stakeholders to deliver trusted and governed data products. Support AI and machine learning initiatives by preparing high-quality training datasets and enabling MLOps workflows.<br>Required Experience5+ years of experience in Data Engineering. Strong experience designing and building ETL/ELT pipelines at scale. Advanced expertise in SQL and Python. Hands-on experience with cloud data platforms, preferably Azure. Experience with modern data warehousing and lakehouse architectures. Exposure to CI/CD and infrastructure automation practices.<br>Top Skills for the Ideal Candidate Microsoft Fabric Azure Data Factory (ADF) Databricks PySpark Python Advanced SQLLakehouse Architecture Delta Lake Azure Synapse Analytics Terraform Infrastructure as Code (IaC) Git Hub Actions Azure Dev Ops Data Governance Data Quality Frameworks Change Data Capture (CDC) API Integrations Streaming Data Pipelines MLOps Enablement Metadata Management Data Lineage<br>Nice to Have Scala Hadoop ecosystem exposure Machine Learning pipeline experience Experience supporting enterprise AI initiatives<br>If you enjoy solving complex data challenges and building platforms that enable data-driven decision making at scale, we would love to hear from you.#Data Engineer #Senior Data Engineer #Azure #Microsoft Fabric #Databricks #PySpark #Data Engineering #Machine Learning #AI #Analytics #Cloud Engineering #UAEJobs #Hiring

Pipeline Integrity Engineer — Digital Twin / Pi-Twin Program ???? Abu Dhabi, UAE (on-site / hybrid) · Full-time About the role Neurula Technologies is building Pi-Twin, an AI-driven pipeline integrity digital twin that fuses real-time sensor data with physics-based modeling to predict, localize, and quantify pipeline threats before they escalate. We're deploying the platform on a flagship program with large organization and are hiring a Pipeline Integrity Engineer to sit at the intersection of integrity engineering, sensing technology, and data science. You'll be part of the integrity domain expert on the team — translating real-world pipeline physics, inspection data, and threat assessment into the logic that drives our digital twin, and working hand-in-hand with the operator's pipeline group through POC and scale-up. What you'll do Own the integrity engineering basis for the Pi-Twin platform: corrosion, erosion, fatigue, mechanical damage, and geotechnical threat models for onshore and subsea pipelines Translate inspection and monitoring data (ILI, DAS/DTS fiber-optic sensing, ultrasonic, acoustic emission, CP/corrosion monitoring) into defect characterization and remaining-life assessment Define and validate acceptance criteria, anomaly thresholds, and alarm logic with the operator's integrity team Work alongside data scientists and ML engineers to ground physics-informed models in real pipeline behavior, including multiphase flow and pressure/temperature dynamics Support fitness-for-service and defect assessment (e.g., ASME B31G/Modified B31G, API 579, DNV) and risk-based inspection planning Contribute to the subsea POC: instrumentation layout, field checklists, commissioning, and interpretation of sensor results Interface directly with client side engineers and act as a technical point of contact during reviews and site activities What you bring Bachelor's or Master's in Mechanical, Petroleum, Materials, Chemical, or related engineering3+ years in pipeline integrity management within oil & gas (operator, EPC, or specialist integrity firm) Strong command of integrity codes and standards: ASME B31.4/B31.8, API 1160/1163, DNV-ST-F101, and corrosion/RBI methodologies Hands-on experience with one or more monitoring/inspection technologies (ILI, fiber-optic DAS/DTS, UT, AE, CP) Working understanding of pipeline hydraulics and multiphase flow Ability to work across disciplines — comfortable explaining integrity concepts to data scientists and software engineers Excellent written and verbal communication for operator-facing technical documentation Nice to have Direct experience in the UAE / GCC oil & gas sector or with ADNOC operating companies and specifications Subsea pipeline integrity exposure Familiarity with digital twin, predictive analytics, or condition-based monitoring platforms Exposure to physics-informed / data-driven modeling concepts Relevant certifications (API 1169, NACE/AMPP corrosion, etc.) Why Neurula Join a small, high-velocity team building category-defining technology for one of the world's largest energy operators. You'll have real ownership, direct access to a marquee client, and the chance to shape a platform from POC to production.

Pipeline Integrity Engineer — Digital Twin / Pi-Twin Program ???? Abu Dhabi, UAE (on-site / hybrid) · Full-time About the role Neurula Technologies is building Pi-Twin, an AI-driven pipeline integrity digital twin that fuses real-time sensor data with physics-based modeling to predict, localize, and quantify pipeline threats before they escalate. We're deploying the platform on a flagship program with large organization and are hiring a Pipeline Integrity Engineer to sit at the intersection of integrity engineering, sensing technology, and data science. You'll be part of the integrity domain expert on the team — translating real-world pipeline physics, inspection data, and threat assessment into the logic that drives our digital twin, and working hand-in-hand with the operator's pipeline group through POC and scale-up. What you'll do Own the integrity engineering basis for the Pi-Twin platform: corrosion, erosion, fatigue, mechanical damage, and geotechnical threat models for onshore and subsea pipelines Translate inspection and monitoring data (ILI, DAS/DTS fiber-optic sensing, ultrasonic, acoustic emission, CP/corrosion monitoring) into defect characterization and remaining-life assessment Define and validate acceptance criteria, anomaly thresholds, and alarm logic with the operator's integrity team Work alongside data scientists and ML engineers to ground physics-informed models in real pipeline behavior, including multiphase flow and pressure/temperature dynamics Support fitness-for-service and defect assessment (e.g., ASME B31G/Modified B31G, API 579, DNV) and risk-based inspection planning Contribute to the subsea POC: instrumentation layout, field checklists, commissioning, and interpretation of sensor results Interface directly with client side engineers and act as a technical point of contact during reviews and site activities What you bring Bachelor's or Master's in Mechanical, Petroleum, Materials, Chemical, or related engineering3+ years in pipeline integrity management within oil & gas (operator, EPC, or specialist integrity firm) Strong command of integrity codes and standards: ASME B31.4/B31.8, API 1160/1163, DNV-ST-F101, and corrosion/RBI methodologies Hands-on experience with one or more monitoring/inspection technologies (ILI, fiber-optic DAS/DTS, UT, AE, CP) Working understanding of pipeline hydraulics and multiphase flow Ability to work across disciplines — comfortable explaining integrity concepts to data scientists and software engineers Excellent written and verbal communication for operator-facing technical documentation Nice to have Direct experience in the UAE / GCC oil & gas sector or with ADNOC operating companies and specifications Subsea pipeline integrity exposure Familiarity with digital twin, predictive analytics, or condition-based monitoring platforms Exposure to physics-informed / data-driven modeling concepts Relevant certifications (API 1169, NACE/AMPP corrosion, etc.) Why Neurula Join a small, high-velocity team building category-defining technology for one of the world's largest energy operators. You'll have real ownership, direct access to a marquee client, and the chance to shape a platform from POC to production.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p><strong>Job Description:</strong></p><br><p>Prof. Mohamed Hamouda’s Integrated Water Cycle Lab invites applications for a research associate starting September 2026 to work on a research project in the area of Remote Sensing of Water Quality. The role focuses on: · Processing and analysis of multi-sensor satellite data (e.g., MODIS, Sentinel, Landsat, PRISMA) · Integration of remote sensing and in-situ datasets · Development and implementation of machine learning and physics-informed models · Assisting in model validation, visualization, and development of early warning tools · Preparing technical reports, journal publications, and project documentation · Coordinating with research partners and supporting field campaigns </p><br><p><strong>Minimum Qualifications:</strong></p><br><p>· Master’s degree in Environmental Engineering, Civil Engineering, Remote Sensing, Data Science, or a related field (PhD preferred) · Minimum 1–3 years of research or industry experience in a relevant field · Experience in remote sensing data processing and GIS · Strong programming skills in Python, MATLAB, or R · Experience with machine learning techniques and data analysis · Strong technical writing and communication skills </p><br><p><strong>Preferred Qualifications:</strong></p><br><p>· Experience with water quality modeling or oceanographic data · Familiarity with satellite platforms (MODIS, Sentinel, Landsat, hyperspectral data) · Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) · Knowledge of physics-informed machine learning or environmental modeling · Experience working on projects in arid or coastal environments (UAE/Gulf region preferred) </p><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>• Ensure exterior and interior cleaning done on all vehicles reporting to our workshop to enhance customer satisfaction<br>Responsibilities:<br>Functional Roles and Responsibilities<br>• Ensure vehicles are washed through car wash machine or manually to ensure all dirt is removed using necessary chemicals (soap) / methods.<br>• Use available chemicals/methods to properly clean the interior.<br>• Maintain the wash area free of mud and dust. Periodically clean that area to remove the sludge and follow safety and health standards.<br>• Maintain vacuum cleaner on daily basis to ensure trouble free running of the machine.<br>• Assist the suppliers whenever they come to service the equipment and also get trained by them.<br>• Ensure that unauthorized vehicles are not washed and that unauthorized persons are not allowed to operate the car wash machine.<br>• Ensure that all consumables are used with utmost care keeping in mind to avoid any wastage. Recycle consumables/ process wherever possible.<br>• Park the vehicle (only if allowed to drive) in appropriate place after washing/ cleaning. Assist drivers to identify vehicles in rush hours.<br>• Ensure customer’s belongings are kept in the same place and preset radio stations are not altered.<br>Qualifications:<br>Education/Certification and Continued Education<br>• High School Certificate.<br>Knowledge and Skills<br>• Should have good physique and health<br>• Positive attitude towards heard work</span> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We are looking for a highly qualified and certified HSE Trainer to join our premier third-party inspection and training company in Abu Dhabi. The ideal candidate will deliver top-tier safety training, conduct practical operator assessments, and ensure compliance with UAE regulatory and international safety standards.</p><br><p>Safety Training Delivery: Conduct comprehensive classroom and practical training sessions, including First Aid, Fire Fighting, Rigging &amp; Slinging, Scaffolding Erection &amp; Dismantling, and Working at Heights.</p><br><p>Operator Assessment: Assess and certify heavy equipment and machinery operators (e.g., Forklifts, Cranes, MEWPs) as per international and local standards.</p><br><p>Curriculum Development: Design and update training materials, manuals, and practical evaluation checklists.</p><br><p>Compliance: Ensure all training programs align with UAE authorities, ADNOC, and international standards (e.g., OSHA, NEBOSH, IOSH, STI).</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>Education: Bachelor’s degree or equivalent in Occupational Health and Safety, Engineering, or a related field.</p><br><p>Experience: Minimum 2-4 years of proven HSE training and operational assessment experience, ideally within a third-party inspection or oil &amp; gas environment in the UAE.</p><br><p>UAE Driver’s License: Mandatory</p><p></p></section>

Role: Data Annotator (Remote) Location: Remote (Work from Anywhere) Job Type: Contract Payout: $6 - $10/hour<br>Role Overview:We are hiring for one of our clients, seeking a Data Annotator to work on a contract basis. The role involves tagging and labeling data to improve machine learning models. This includes processing text, images, and audio for AI training purposes.<br>Key Responsibilities:• Review and annotate text, images, or audio data according to provided guidelines.• Ensure accuracy and consistency in labeling to support model performance.• Follow established annotation protocols and maintain quality standards.• Collaborate with team members to clarify annotation tasks when needed.• Meet daily or weekly productivity targets for annotated data output.<br>Required Skills & Qualifications:• Proficiency in data annotation tools and platforms.• Strong attention to detail for accurate labeling and tagging.• Basic understanding of machine learning and AI concepts.• Ability to follow structured guidelines for consistent results.• Self-motivated with the discipline to work independently in a remote setting.<br>More About the Opportunity:This role offers a unique opportunity to work with a global leader in the Technology, Information and Internet industry, contributing to the development of cutting-edge AI systems. The position supports scalable data processing for machine learning applications.<br>Equal Opportunity Employer:We hire based on skills and expertise. All qualified candidates are welcome regardless of background, experience, or prior employment history. Applications are reviewed solely on demonstrated technical ability and qualifications.<br>Apply Now!

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><ol><li><p>Data Analysis &amp; Insight Generation</p></li></ol><p>Analyze large datasets to identify trends and generate actionable insights for decision making and operational efficiency.</p><p>Communicate findings through visualizations and clear storytelling.</p><ol><li><p>Machine Learning &amp; Model Development</p></li></ol><p>Develop and deploy machine learning models for use cases such as forecasting, optimization, and risk analysis.</p><p>Apply statistical and machine learning techniques to solve complex business problems.</p><ol><li><p>Data Preparation &amp; Feature Engineering</p></li></ol><p>Prepare data through extraction, cleaning, preprocessing, and feature engineering.</p><p>Ensure data quality and integrity for reliable model performance.</p><ol><li><p>Model Deployment &amp; Monitoring</p></li></ol><p>Deploy models into production and monitor performance for drift or degradation.</p><p>Continuously improve models based on feedback and new data.</p><ol><li><p>Collaboration &amp; Stakeholder Engagement</p></li></ol><p>Work with business teams to translate requirements into analytical solutions.</p><p>Collaborate with Data Engineering and Data Governance teams for end to end delivery.</p><ol><li><p>AI Governance</p></li></ol><p>Ensure all AI and machine learning activities comply with governance, privacy, and regulatory requirements by following defined lifecycle processes, risk classification, and using approved governed data.</p><p>Implement responsible and secure AI practices, including bias and fairness checks, explainability, model documentation, auditability, and collaboration with Cybersecurity and Data Governance teams.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li><p>Minimum Qualifications</p><ul><li><p>Bachelor's or Master's Degree in Data Science, Artificial Intelligence (AI), Statistics, Computer Science, or a related field.</p></li></ul><p>Minimum Experience</p><ul><li><p>Minimum <strong>5+ years</strong> of experience in Data Science, Machine Learning, Artificial Intelligence, or Advanced Analytics.</p></li><li><p>Proven experience developing, deploying, and maintaining machine learning models in production environments.</p></li><li><p>Experience working with large-scale datasets and cloud-based analytics platforms is preferred.</p></li></ul><p>Skills &amp; Competencies</p><ul><li><p>Strong programming skills in <strong>Python</strong> (preferred) or <strong>R</strong>.</p></li><li><p>Experience with large-scale data processing using <strong>SQL</strong>, <strong>Spark</strong>, or similar technologies.</p></li><li><p>Hands-on experience with machine learning frameworks such as <strong>TensorFlow</strong>, <strong>PyTorch</strong>, and <strong>Scikit-learn</strong>.</p></li><li><p>Experience in end-to-end machine learning model development, validation, deployment, and optimization.</p></li><li><p>Knowledge of <strong>MLOps</strong> practices, including CI/CD pipelines, model monitoring, version control, and automated retraining.</p></li><li><p>Understanding of data engineering concepts, data pipelines, and cloud data platforms, preferably <strong>Microsoft Azure</strong> and <strong>Databricks</strong>.</p></li><li><p>Strong knowledge of statistical analysis, predictive modeling, feature engineering, and data preprocessing techniques.</p></li><li><p>Experience using data visualization tools such as <strong>Power BI</strong> and <strong>Tableau</strong> to communicate analytical insights.</p></li><li><p>Understanding of data governance, data quality management, privacy regulations, and AI governance principles.</p></li><li><p>Strong analytical thinking, problem-solving, and critical reasoning skills.</p></li><li><p>Excellent communication, presentation, and stakeholder management skills.</p></li><li><p>Ability to work collaboratively with cross-functional teams in an agile environment.</p></li><li><p>Strong organizational skills with the ability to manage multiple priorities and deliver high-quality outcomes within deadlines.</p></li></ul></li></ul><p></p></section>

ADIC is seeking a Quantitative Researcher to join the Strategy team. The successful candidate will play a key role in supporting ADIC's investment process through quantitative research, model development, and AI-driven solutions.<br><br>This role offers the opportunity to contribute to investment decision-making across both public and private markets by developing systematic signals, valuation models, and portfolio construction tools. The successful candidate will work closely with investment professionals across the Strategy team to enhance quantitative capabilities and support the development of innovative investment solutions.<br><br>Key Responsibilities<br><br> Generate and test alpha signals and factor ideas across asset classes using statistical and machine learning techniques. Conduct quantitative research and develop valuation models across both public and private markets. Design, backtest, and evaluate quantitative models, systematic strategies, and portfolio construction frameworks. Build and enhance risk models, performance attribution frameworks, and investment analytics. Develop end-to-end quantitative tools and applications to support investment workflows, from data ingestion through to deployment. Partner with investment professionals across the Strategy team to deliver research, model specifications, and quantitative insights. Drive AI and machine learning initiatives, identifying opportunities to enhance research and investment processes. <br><br>Requirements<br><br>Experience<br><br> Minimum 5 years of relevant experience in quantitative research, systematic investing, portfolio construction, asset allocation, or investment strategy. Experience conducting quantitative research across public markets, with exposure to private markets considered advantageous. Proven experience designing, backtesting, and implementing quantitative models or systematic investment strategies. Experience applying AI and machine learning techniques to financial datasets and developing production-ready analytical tools. <br><br>Education<br><br> Bachelor's degree in Finance, Mathematics, Engineering, Computer Science, Statistics, Physics, or another quantitative discipline. Master's degree or PhD is considered a strong advantage. <br><br>Technical Skills & Knowledge<br><br> Strong programming skills in Python or another object-oriented language, with experience developing production-quality code. Good understanding of quantitative modelling, time-series analysis, factor models, and portfolio optimisation. Experience with machine learning frameworks such as scikit-learn, Tensor Flow or PyTorch. Knowledge of SQL, cloud platforms, and Git-based development practices. Strong understanding of financial markets, including equities, fixed income, private markets, and their application to portfolio management and asset allocation. Excellent analytical and communication skills, with the ability to present complex quantitative findings to investment stakeholders.

Job Summary We are seeking an experienced Data & AI Senior Specialist to design, develop, and deliver enterprise AI and data solutions that support business transformation. This is a hands-on technical role responsible for building scalable data platforms, AI applications, machine learning models, and advanced analytics solutions while providing technical leadership and mentoring team members. The ideal candidate will have strong expertise in data engineering, cloud technologies, AI/ML, and Generative AI, with the ability to translate business requirements into innovative, production-ready solutions.<br>Key Responsibilities Design, develop, and maintain enterprise data platforms, data pipelines, data warehouses, and AI-driven solutions. Build, deploy, monitor, and optimize machine learning models, Generative AI applications, and advanced analytics solutions. Write production-quality code, develop prototypes, troubleshoot complex technical issues, and support critical AI and data systems. Define data architecture, engineering standards, AI frameworks, and best practices for coding, testing, security, MLOps, and data governance. Evaluate emerging technologies and provide recommendations on architecture, platforms, and technical solutions. Collaborate with business stakeholders to identify AI opportunities, define solution requirements, and deliver measurable business value. Present technical updates, risks, and recommendations to senior stakeholders. Mentor technical team members through code reviews, technical guidance, and knowledge sharing. Ensure compliance with data governance, information security, privacy regulations, and responsible AI practices. Drive continuous improvement in data quality, AI governance, and operational excellence.<br><br>Requirements Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, or a related field (minimum 6 years' experience), or a Diploma with minimum 7 years' experience in Data Engineering, Data Science, Artificial Intelligence, or related disciplines. Proven experience delivering enterprise AI, machine learning, and data engineering solutions in production environments. Strong hands-on experience with Python, advanced SQL, machine learning, deep learning, NLP, Generative AI, LLMs, and Retrieval-Augmented Generation (RAG). Experience designing scalable ETL/ELT pipelines, enterprise data platforms, and cloud-based solutions using Azure, AWS, GCP, or OCI. Knowledge of MLOps, CI/CD, containerization, model deployment, monitoring, and data governance practices. Strong analytical, problem-solving, stakeholder management, and communication skills. Experience mentoring technical teams and working collaboratively across business and technology functions.

Job Title: Data Scientist Location: Abu Dhabi (On site)**This role requires relocation to Abu Dhabi**<br>We’re hiring Data Scientists to join one of our clients. If you’re passionate about turning data into meaningful insights and building impactful AI solutions, we’d love to hear from you.<br>What you’ll be doing In this role, you’ll design and develop scalable machine learning models and AI-driven solutions that tackle complex business challenges and support smarter decision-making.<br>Key Responsibilities Work with large, complex datasets to solve real-world business problems Collect, clean, and preprocess data for analysis and model training Perform exploratory data analysis (EDA) to uncover insights and guide model development Build, train, and optimize machine learning models using modern algorithms and frameworks Develop end-to-end ML pipelines, from data ingestion to model deployment Automate model training, testing, and deployment using CI/CD and MLOps tools Collaborate with cross-functional teams to integrate models into production systems and deliver complete solutions<br>What we’re looking for5+ years of experience in data science, machine learning, or AIStrong knowledge of supervised and unsupervised learning, deep learning, and areas such as NLP, computer vision, or generative AI (including LLMs) Proficiency in Python, with working knowledge of SQLExperience building data pipelines and working with big data tools (e.g. Spark, Airflow, Hadoop) Understanding of model serving, APIs (Fast API, Flask), and optimizing models for real-time or batch inference Familiarity with Docker, Kubernetes, CI/CD pipelines, and MLOps tools such as MLflow or Kubeflow Experience deploying models on cloud platforms like AWS, Google Cloud, or Azure (e.g. Sage Maker, Vertex AI) Bachelor’s degree in Computer Science, Engineering, or a related field<br>If this sounds like the right next step for you, apply now!

Job Title: Data Scientist Location: Abu Dhabi (On site)**This role requires relocation to Abu Dhabi**<br>We’re hiring Data Scientists to join one of our clients. If you’re passionate about turning data into meaningful insights and building impactful AI solutions, we’d love to hear from you.<br>What you’ll be doing In this role, you’ll design and develop scalable machine learning models and AI-driven solutions that tackle complex business challenges and support smarter decision-making.<br>Key Responsibilities Work with large, complex datasets to solve real-world business problems Collect, clean, and preprocess data for analysis and model training Perform exploratory data analysis (EDA) to uncover insights and guide model development Build, train, and optimize machine learning models using modern algorithms and frameworks Develop end-to-end ML pipelines, from data ingestion to model deployment Automate model training, testing, and deployment using CI/CD and MLOps tools Collaborate with cross-functional teams to integrate models into production systems and deliver complete solutions<br>What we’re looking for5+ years of experience in data science, machine learning, or AIStrong knowledge of supervised and unsupervised learning, deep learning, and areas such as NLP, computer vision, or generative AI (including LLMs) Proficiency in Python, with working knowledge of SQLExperience building data pipelines and working with big data tools (e.g. Spark, Airflow, Hadoop) Understanding of model serving, APIs (Fast API, Flask), and optimizing models for real-time or batch inference Familiarity with Docker, Kubernetes, CI/CD pipelines, and MLOps tools such as MLflow or Kubeflow Experience deploying models on cloud platforms like AWS, Google Cloud, or Azure (e.g. Sage Maker, Vertex AI) Bachelor’s degree in Computer Science, Engineering, or a related field<br>If this sounds like the right next step for you, apply now!

Job Title: Data Scientist Location: Abu Dhabi (On site)**This role requires relocation to Abu Dhabi**<br>We’re hiring Data Scientists to join one of our clients. If you’re passionate about turning data into meaningful insights and building impactful AI solutions, we’d love to hear from you.<br>What you’ll be doing In this role, you’ll design and develop scalable machine learning models and AI-driven solutions that tackle complex business challenges and support smarter decision-making.<br>Key Responsibilities Work with large, complex datasets to solve real-world business problems Collect, clean, and preprocess data for analysis and model training Perform exploratory data analysis (EDA) to uncover insights and guide model development Build, train, and optimize machine learning models using modern algorithms and frameworks Develop end-to-end ML pipelines, from data ingestion to model deployment Automate model training, testing, and deployment using CI/CD and MLOps tools Collaborate with cross-functional teams to integrate models into production systems and deliver complete solutions<br>What we’re looking for5+ years of experience in data science, machine learning, or AIStrong knowledge of supervised and unsupervised learning, deep learning, and areas such as NLP, computer vision, or generative AI (including LLMs) Proficiency in Python, with working knowledge of SQLExperience building data pipelines and working with big data tools (e.g. Spark, Airflow, Hadoop) Understanding of model serving, APIs (Fast API, Flask), and optimizing models for real-time or batch inference Familiarity with Docker, Kubernetes, CI/CD pipelines, and MLOps tools such as MLflow or Kubeflow Experience deploying models on cloud platforms like AWS, Google Cloud, or Azure (e.g. Sage Maker, Vertex AI) Bachelor’s degree in Computer Science, Engineering, or a related field<br>If this sounds like the right next step for you, apply now!