mechanical engineer

estimation engineer

sales engineer

ai engineer

infrastructure engineer

machine learning engineer

TALENTMATE

<div>
 
 Job Description
 
 
 
 
 About Us
 
 
 
 At Dyson, we&rsquo;re driven by a relentless pursuit of innovation&mdash;pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson&rsquo;s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.
 
 
 You&rsquo;ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.
 
 
 
 About the role
 
 
 We are looking for a specialized Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Architect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.
 </li>
 <li>
 Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.
 </li>
 <li>
 Quality Assurance &amp; Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.
 </li>
 <li>
 Tooling &amp; Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.
 </li>
 <li>
 Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.
 </li>
 <li>
 Set up and maintain robust data preparation infrastructure&mdash;optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.
 </li>
 <li>
 Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You&rsquo;ll help transform raw data into actionable insight, supporting both research and deployment.
 </li>
 <li>
 Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.
 
 
 </li>
 </ul>
 
 About you
 
 
 
 <ul>
 <li>
 At least 3+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.
 </li>
 <li>
 Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).
 </li>
 <li>
 Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).
 </li>
 <li>
 Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).
 </li>
 <li>
 Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.
 </li>
 <li>
 Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.
 </li>
 <li>
 Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.
 </li>
 <li>
 Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).
 </li>
 <li>
 Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).
 </li>
 <li>
 Strong background in feature engineering, data analysis, and data visualization&mdash;comfortable using tools like Jupyter, Tableau, or Power BI.
 </li>
 <li>
 Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.
 </li>
 <li>
 Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.
 </li>
 <li>
 Bachelor&rsquo;s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.
 
 
 </li>
 </ul>
 Dyson is an equal opportunity employer. We know that great minds don&rsquo;t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.
 
 
 Job Details
 
 
 Role Level: Not Applicable Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: http://careers.dyson.com Job Function: Engineering Company Industry/
 
 
 Sector: Appliances Electrical and Electronics Manufacturing
 
 
 What We Offer
 
 
 
 About The Company
 
 
 
 Searching, interviewing and hiring are all part of the professional life. The TALENTMATE Portal idea is to fill and help professionals doing one of them by bringing together the requisites under One Roof. Whether you're hunting for your Next Job Opportunity or Looking for Potential Employers, we're here to lend you a Helping Hand.
 
 
 Report
 
 
 Disclaimer: talentmate.com is only a platform to bring jobseekers &amp; employers together. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal or bank related information. We also recommend you visit Security Advice for more information. If you suspect any fraud or malpractice, email us at abuse@talentmate.com.
</div>

Data Intelligence Machine Learning Engineer

MultiBank Group

<div>
 
 Welcome to
 
 MultiBank Group
 
 , a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
 
 
 
 
 
 Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
 
 
 
 
 
 
 Role Overview:
 
 
 
 
 
 
 We are seeking an experienced
 
 AI Data Engineer
 
 to design, develop, and deploy innovative data and machine learning solutions that drive customer engagement, retention, and lifetime value (LTV). This role will focus on building scalable data pipelines, predictive models, and GenAI-powered applications that enable more personalised trading experiences and support data-driven decision-making across the business.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 <ul>
 <li>
 Collaborate with the wider marketing department to build meaningful datasets and a centralised data warehouse that will be used for reporting across numerous teams, focused on customer retention and LTV.
 </li>
 <li>
 Develop and own machine learning solutions that specialise in customer personalisation to increase engagement and coordinate with marketing teams towards their strategy and execution across multiple channels, especially around predictive modelling, churn prediction and customer segmentation.
 </li>
 <li>
 Explore the capabilities of Gen AI to develop new apps for our traders that make trading easier and more personalised based on their preferences.
 </li>
 <li>
 Maintain a commercial acumen and find opportunities where technology can be used to increase customer engagement or automate internal tasks.
 </li>
 </ul>
 
 
 
 
 
 Qualifications &amp; Requirements:
 
 
 
 
 
 <ul>
 <li>
 Strong expertise in SQL, comfortable with raw data and multiple high-volume datasets such as customer journey, marketing performance or product behaviour.
 </li>
 <li>
 Comfortable creating pipelines and automations with Python to connect multiple endpoints and APIs such as first party databases, marketing platforms or other data collection platforms.
 </li>
 <li>
 Expertise in using Python todeploy machine learning solutions end to end, especially around predictive modelling and customer segmentation.
 </li>
 <li>
 Previous experience in finding customer insights through data analysis, communicating it to different stakeholders and strategizing on how to increase customer engagement and LTV.
 </li>
 <li>
 Capable of creating applications using LLMs that summarise high volumes of data and knowledge of the latest Gen AI use cases.
 </li>
 <li>
 Previous exposure to
 
 ETL tools
 
 (e.g., dbt, AWS Glue) and cloud environments (preferably
 
 AWS, SageMaker
 
 ).
 </li>
 <li>
 Strong communication skills with the ability to present complex data insights to non-technical stakeholders and support business strategy.
 </li>
 </ul>
 
 
 
 
 
 Why Join Us?
 
 
 
 
 
 <ul>
 <li>
 Work with an industry-leading global financial institution.
 </li>
 <li>
 Competitive salary and comprehensive employee benefits.
 </li>
 <li>
 Opportunities for professional growth and career advancement.
 </li>
 <li>
 Collaborative, inclusive, and dynamic work environment.
 </li>
 <li>
 Commitment to innovation and professional excellence.
 </li>
 </ul>
 
 
 
 
 
 Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
 
 
</div>

AI Data Engineer

Fuse Energy

<div>Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more. 
 
We&rsquo;re creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers. 
 
But we&rsquo;re not stopping there. We&rsquo;re also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries. 
 
We're now looking to establish a cutting-edge AI team. As an Applied AI Engineer, this position is ideal for someone who possesses the technical expertise of a backend engineer but is specifically interested in applied AI and how it can be used to enhance the energy experience for our customers and our internal operations. You'll be working on a variety of exciting projects, including consumer-focused features like the Energy Co-Pilot and the Speedy Onboarding process (leveraging tools such as VLM/LLM). You will also collaborate across teams to build AI tools that enhance productivity and streamline processes within Fuse. 
 
Responsibilities<ul><li>
Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)</li><li>
Build and optimise internal AI tools that will make the whole company more productive with a focus on automation and enhancing workflows</li><li>
Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms</li><li>
Collaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricing</li><li>
Improve AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecasts</li><li>
Stay up to date with the latest advancements in applied AI and machine learning and apply them to solve real-world problems within the energy space</li>
Monitor the performance of AI tools and models, ensuring they are functioning efficiently and effectively 
<li>
</li></ul> 
 
Requirements 
<ul><li>
Minimum 3 years of engineering experience</li><li>
Proven experience as a Backend Engineer with a strong interest and practical experience in applied AI or machine learning</li><li>
Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.)</li><li>
Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into production</li><li>
Solid understanding of cloud technologies, containerisation and building scalable AI applications</li><li>
Ability to integrate AI/ML models into real-world applications, focusing on usability and performance</li><li>
Strong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environment</li><li>
Experience working with large datasets, particularly in relation to demand and supply forecasting</li></ul>
Bonus<ul><li>
Experience or strong interest in energy markets and trading strategies</li><li>
Understanding of weather forecasting, energy demand patterns, and production modelling</li><li>
Exposure to Natural Language Processing (NLP) or other related fields</li></ul> 

Benefits 
<ul><li>
Competitive salary and an equity sign-on bonus</li><li>
Biannual bonus scheme</li><li>
Fully expensed tech to match your needs</li><li>
Paid annual leave</li><li>
Breakfast and dinner allowance for office based employees</li></ul></div>

Applied AI Engineer

Ministry of Economy & Tourism

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

خبير الذكاء الاصطناعي - Artificial Intelligence Expert

Tata Consultancy Services

<div>
 
 
 Job Title
 
 &ndash; AI Engineer
 
 
 
 Company
 
 &ndash; TCS (MEA)
 
 
 
 Location
 
 &ndash; Dubai
 
 
 
 Job type
 
 &ndash; Full time
 
 
 
 
 
 
 About Us:
 
 
 
 Tata Consultancy Services (TCS) is an IT services, consulting and business solutions organization that has been partnering with many of the world&rsquo;s largest businesses in their transformation journeys for over 50 years. TCS offers a consulting-led, cognitive powered, integrated portfolio of business, technology and engineering services and solutions. This is delivered through its unique Location Independent Agile&trade; delivery model, recognized as a benchmark of excellence in software development.
 
 
 A part of the Tata group, India's largest multinational business group, TCS has over 616,171 of the world&rsquo;s best-trained consultants with 157 nationalities in 53 countries. For more information, visit www.tcs.com and follow TCS news at @TCS_News.
 
 
 
 
 
 
 
 Job Description:
 
 
 
 
 
 
 
 
 Key Accountabilities:
 
 
 <ul>
 <li>
 
 AI Solution Design &amp; Development:
 
 </li>
 <li>
 Design, build, and deploy AI-powered applications using Azure AI Services, including Azure OpenAI Service, Azure Machine Learning, Azure Cognitive Services (Speech, Vision, Language), Azure AI Search, Azure Functions, and Azure Databricks.
 </li>
 <li>
 
 LLM Integration &amp; Generative AI:
 
 </li>
 <li>
 Develop and integrate Large Language Model (LLM) solutions using Azure OpenAI endpoints (GPT-4.1, GPT-4o, GPT-4o-mini) routed through FAB's centralized AI Hub gateway for governance, observability, and capacity management. Build enterprise use cases such as knowledge search, document intelligence, content summarization, call analytics, sentiment analysis, and workflow automation.
 </li>
 <li>
 
 Python Engineering &amp; Backend Development:
 
 </li>
 <li>
 Write clean, modular, and production-grade Python code for AI/ML model development, API integrations, data processing pipelines, backend services, and automation workflows using frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, and FastAPI.
 </li>
 <li>
 
 RAG &amp; Semantic Retrieval:
 
 </li>
 <li>
 Implement Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector search, semantic retrieval architectures, prompt engineering, and evaluation techniques for enterprise knowledge mining and document intelligence.
 </li>
 <li>
 
 Agentic AI Development:
 
 </li>
 <li>
 Design and develop intelligent agentic AI systems capable of planning, reasoning, tool execution, and orchestration across enterprise systems using FAB's GERNAS OS platform and Agent Development Kit (ADK) in a secure and governed manner.
 </li>
 <li>
 
 Model Evaluation &amp; Responsible AI:
 
 </li>
 <li>
 Implement model evaluation metrics for accuracy, hallucination detection, bias, latency, and throughput in alignment with FAB's Responsible AI framework. Ensure AI solutions comply with FAB's security, data privacy, model governance, and regulatory requirements, including controls for accuracy, hallucination, bias, latency, and resilience.
 </li>
 <li>
 
 Deployment &amp; Production Operations:
 
 </li>
 <li>
 Deploy, monitor, and optimize AI solutions in production environments using CI/CD practices, containerization, observability, logging, performance monitoring, and cost optimization techniques.
 </li>
 <li>
 
 Collaboration &amp; Stakeholder Engagement:
 
 </li>
 <li>
 Collaborate with data scientists, platform engineers, DevOps/MLOps engineers, business analysts, and product teams to convert business requirements into scalable AI solutions.
 </li>
 <li>
 
 Innovation &amp; Continuous Learning:
 
 </li>
 <li>
 Continuously evaluate emerging Azure AI, Generative AI, and Agentic AI capabilities and recommend practical adoption opportunities aligned with FAB's AI strategy. Stay abreast of state-of-the-art developments in generative AI and agentic architectures.
 </li>
 </ul>
 
 
 
 
 
 TECHNICAL SKILLS: minimum 3-4 yrs of working experience mandatory
 
 
 
 
 Azure AI Services:
 
 Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks.
 
 
 
 Python Programming:
 
 Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI).
 
 
 
 LLM &amp; Generative AI:
 
 Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques.
 
 
 
 ML Libraries &amp; Frameworks:
 
 Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and NLP libraries (spaCy, NLTK).
 
 
 
 Vector Databases:
 
 Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone.
 
 
 
 DevOps/MLOps:
 
 Hands-on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights.
 
 
 
 Cloud Security &amp; Integration:
 
 Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns.
 
 
 
 AI Ethics &amp; Governance:
 
 Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems.
 
 
 
 
 
 
 KNOWLEDGE, SKILLS, &amp; EXPERIENCE
 
 
 
 
 
 Minimum Qualifications:
 
 
 
 
 Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field; Master's degree is preferred. Microsoft Certified: Azure AI Engineer Associate (AI-102) certification is highly preferred.
 
 
 
 
 Minimum Experience:
 
 
 
 
 3+ years of hands-on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments.
 
 
 Mandatory hands-on experience with Microsoft Azure AI Services.
 
 
 Experience working with large-scale datasets and real-time enterprise data.
 
 
 Experience in financial services, banking, risk, compliance, customer service, or regulated enterprise environments is an advantage.
 
 
 
 
 Knowledge and Skills:
 
 
 
 
 
 Business Understanding:
 
 
 
 Strong understanding of business processes and the ability to identify opportunities for AI-driven optimization and automation across banking domains.
 
 
 
 Analytical &amp; Problem-Solving:
 
 
 
 Excellent analytical, problem-solving, debugging, and performance optimization skills with the ability to troubleshoot AI applications in production and translate complex business problems into AI solutions.
 
 
 
 Communication Skills:
 
 
 
 Strong verbal and written communication skills, capable of explaining complex AI concepts to both technical and non-technical stakeholders.
 
 
 
 Collaboration:
 
 
 
 Proven ability to work effectively in cross-functional teams, collaborating with data scientists, platform engineers, DevOps engineers, business analysts, and product teams.
 
 
 
 Responsible AI Mindset:
 
 
 
 Understanding of AI governance, model risk, data privacy, security, and compliance requirements in a regulated banking environment.
 
 
 
 Production Engineering:
 
 
 
 Ability to build, deploy, monitor, and optimize production-grade AI systems with attention to reliability, scalability, cost, and operational excellence.
 
 
 
 Adaptability &amp; Learning:
 
 
 
 Willingness to stay updated on the latest AI technologies, agentic frameworks, and cloud services, and the ability to apply them to solve evolving business challenges.
 
 
 Thank you for your interest in applying for this position with TCS. We will review your application and will get back to you if we are considering your interest in this opportunity.
 
 
 
 
 
 
 Application Deadline: 30- July -2026
 
 
 
 
 
 
 
 Privacy Note:
 
 
 
 https://www.tcs.com/connect-with-tcs/privacy-policy
 
</div>

AI Engineer

Huspy

<div>
 
 The Story So Far: We&rsquo;re Building a Global Brand in Real Estate
 
 
 
 Huspy is one of the leading property technology companies in EMEA.
 
 
 Launched in 2020, we now operate in multiple cities across the UAE and Spain, expanding into Saudi Arabia and 3 more European markets by 2026. Today, we own the largest portion of the UAE mortgage market and are one of the fastest-growing players in every European city we&rsquo;ve entered.
 
 
 We&rsquo;ve raised over $140 million (Series A and Series B) from the world&rsquo;s top investors, including Sequoia Capital, Founders Fund and Balderton Capital, to reshape the homebuying journey through powerful technology and agent-first tools.
 
 
 We&rsquo;ve built a SuperApp that empowers real estate agents and mortgage brokers, bringing cutting‑edge technology to one of the world&rsquo;s most traditional industries. We&rsquo;re transforming how property transactions happen &mdash; faster, smarter, and better for everyone.
 
 
 We&rsquo;re not slowing down. The question is: will you be part of what&rsquo;s next?
 
 
 
 The Main Event: What You&rsquo;ll Drive, Build, and Own
 
 
 
 You will be working closely with Product, Data, and Engineering teams responsible for developing and enhancing AI-powered solutions across our Real Estate Agent Platform and Mortgage Broker Portal. You'll leverage modern machine learning technologies and cloud infrastructure to build intelligent, data-driven products in an innovative and collaborative environment.
 
 
 
 Tech stack:
 
 Python, PostgreSQL, AWS, FastAPI
 
 
 
 Hands-On Engineering:
 
 Contribute to the development, deployment, and optimisation of machine learning models and AI-driven services. Take ownership of key technical deliverables while leading by example in engineering best practices.
 
 
 
 Machine Learning Excellence:
 
 Drive best practices in machine learning development, including data preparation, feature engineering, model training, evaluation, deployment, and monitoring. Ensure solutions are scalable, reliable, and maintainable in production environments.
 
 
 
 Stakeholder Collaboration:
 
 Work closely with Product, Data, Design, and Engineering teams to identify opportunities for AI-driven innovation, translate business requirements into technical solutions, and deliver measurable impact.
 
 
 
 The Perfect Match: What It Takes to Succeed at Huspy
 
 
 
 
 AI/ML Engineering Experience:
 
 Strong technical background in Python and machine learning, with a passion for building intelligent products and solving complex data-driven challenges.
 
 
 
 Product-Focused Mindset:
 
 Ability to work cross-functionally and collaborate with Product, Data, and Engineering teams to deliver impactful AI-powered solutions that enhance customer experiences and business outcomes.
 
 
 
 Technical Expertise:
 
 Experience developing and deploying machine learning models using Python and modern ML frameworks. Strong knowledge of data processing, model lifecycle management, APIs, CI/CD, cloud platforms (AWS preferred), and production-grade software engineering practices. Experience in AI development practices and tools is a must-have.
 
 
 
 Data &amp; Machine Learning Knowledge:
 
 Experience working with structured and unstructured data, feature engineering, model evaluation, experimentation, and performance optimisation. Familiarity with MLOps practices and model monitoring is highly desirable.
 
 
 
 Collaborative Attitude:
 
 Excellent communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders while fostering an inclusive, engaging team environment.
 
 
 
 Work Setup:
 
 Hybrid in Dubai or Madrid, remote anywhere in the EU. Or we offer relocation support to Dubai, if preferred.
 
 
 By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.
 
 
 By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.
</div>

<div>
 
 Job Description
 
 
 
 
 About Revolut
 
 
 
 People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products &mdash; including spending, saving, investing, exchanging, travelling, and more &mdash; help our 75+ million customers get more from their money every day.
 
 
 As we continue our lightning-fast growth,&zwnj; 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work&trade;. So far, we have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. And we're looking for more brilliant people. People who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution.
 
 
 
 About The Role
 
 
 
 The Product team shapes the experiences that power Revolut. They turn complex problems into simple, scalable solutions &mdash; collaborating across Design, Engineering, and Data to build features our customers love.
 
 
 We&rsquo;re looking for a Lead Applied AI Engineer who can manage their product roadmap, including day-to-day operations, project execution, and risk assessment.
 
 
 From conception to launch and beyond, you&rsquo;ll collaborate cross-functionally and communicate with senior management to be the go-to person for your product.
 
 
 Up to shape what's next in finance? Let's get in touch.
 
 
 
 What You'll Be Doing
 
 
 
 <ul>
 <li>
 Owning the product vision, strategy, and roadmap for AI-powered solutions, leveraging LLMs and other machine learning technologies
 </li>
 <li>
 Collaborating closely with Data Scientists and Software Engineers to deliver impactful solutions
 </li>
 <li>
 Leading cross-functional teams to build and deploy NLP and AI solutions, such as AI assistants and AI automation platforms
 </li>
 <li>
 Setting your team's goals, success metrics, and roadmap to align with company goals
 </li>
 <li>
 Delivering measurable results for sophisticated products under ambiguous situations in a fast-paced environment
 
 
 </li>
 </ul>
 
 What You'll Need
 
 
 
 <ul>
 <li>
 Experience developing and launching AI products/features from scratch
 </li>
 <li>
 High analytical and technical acumen, along with solid business sense and problem-solving skills
 </li>
 <li>
 Experience in a data science or machine learning role
 </li>
 <li>
 Experience owning machine learning projects, from design to implementation and iteration
 </li>
 <li>
 Great Python, SQL, or other programming language skills
 </li>
 <li>
 Hands-on experience with deep learning libs (TensorFlow, Keras, PyTorch, etc.)
 </li>
 <li>
 Knowledge of version control, model deployment, and developer environments
 </li>
 <li>
 Evidence of impressive mathematical and statistical knowledge
 </li>
 <li>
 An entrepreneurial drive to never settle
 
 
 </li>
 </ul>
 Building a global financial super app isn&rsquo;t enough. Our Revoluters are a priority, and that&rsquo;s why in 2021 we launched our inaugural D&amp;I Framework, designed to help us thrive and grow everyday. We're not just doing this because it's the right thing to do. We&rsquo;re doing it because we know that seeking out diverse talent and creating an inclusive workplace is the way to create exceptional, innovative products and services for our customers. That&rsquo;s why we encourage applications from people with diverse backgrounds and experiences to join this multicultural, hard-working team.
 
 
 
 Important Notice For Candidates
 
 
 
 Job scams are on the rise. Please keep these guidelines in mind when applying for any open roles.
 
 
 <ul>
 <li>
 Only apply through official Revolut channels. We don&rsquo;t use any third-party services or platforms for our recruitment.
 </li>
 <li>
 Always double-check the emails you receive. Make sure all communications are being done through official Revolut emails, with an @revolut.com domain.
 
 
 </li>
 </ul>
 
 We won't ask for payment or personal financial information during the hiring process.
 
 If anyone does ask you for this, it&rsquo;s a scam. Report it immediately.
 
 
 By submitting this application, I confirm that all the information given by me in this application for employment and any additional documents attached hereto are true to the best of my knowledge and that I have not wilfully suppressed any material fact. I confirm I have disclosed if applicable any previous employment with Revolut. I accept that if any of the information given by me in this application is in any way false or incorrect, my application may be rejected, any offer of employment may be withdrawn or my employment with Revolut may be terminated summarily or I may be dismissed. By submitting this application, I agree that my personal data will be processed in accordance with Revolut's Candidate Privacy Notice
 
 
 Job Details
 
 
 Role Level: Not Applicable Work Type: Full-Time Country: United Arab Emirates City: Dubai Company Website: https://www.revolut.com Job Function: Engineering Company Industry/
 
 
 Sector: Other
 
 
 What We Offer
 
 
 
 About The Company
 
 
 
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</div>

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