75 Machine Learning jobs in the United Arab Emirates

Educational Background: Master's or PhD in Computer Science, Machine Learning, Data Science, or related field. (Or Bachelor's with exceptional, extensive experience.) Strong theoretical foundation in machine learning, algorithms, and statistics.

Experience: 7+ years in data science or ML engineering roles, with at least 2 years in a technical leadership position guiding other engineers or researchers. Proven track record of delivering AI/ML-driven features or products to market.

Technical Mastery: Proficiency in Python and common ML libraries (TensorFlow/PyTorch, scikit-learn, pandas, etc.). Experience with data pipeline tools (Spark, Kafka, or similar) and deploying models in production environments (using cloud services or on-device inference). Solid understanding of both classical algorithms and deep learning techniques.

Domain Knowledge: Experience with time-series data or biosignals is a strong plus (e.g., physiological data, wearable data, or sensor streams). Familiarity with NLP for conversational agents or Q&A systems is beneficial.

Problem Solving & Creativity: Exceptional ability to break down complex problems and invent original solutions. Demonstrated success in tackling hard, open-ended problems with measurable impacts (e.g., improving accuracy, reducing support tickets).

Preferred Experience:

• Health Tech or Related Industries: Experience in healthtech, medtech, or fitness analytics, working on biometric algorithms, predictive health models, or digital therapeutics. Alternatively, experience in high-stakes data domains like finance or autonomous vehicles that require precision.
• Leadership & Communication: Experience presenting findings to executives or non-technical stakeholders, articulating the value of ML initiatives in terms of user impact or ROI.
• Full-Stack ML: Familiarity with the entire ML stack: from signal processing and feature engineering (especially for sensor data) to building customer-facing UI that displays ML results (collaborating with front-end teams).
• Continuous Learning: Evidence of staying current through publications, ML competitions, patents, or open-source contributions. Passion for learning and applying new technologies.

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Are you actively seeking a new job role? Well, you are at the right place! We’re looking for a skilled Machine Learning Expert to join our team and enhance our AI-driven information systems. The ideal candidate will develop intelligent models that optimize database queries and improve our robotics dialogue flow, enabling natural voice-based interactions between users and our robot. This role involves working with large datasets, implementing AI-powered solutions, and collaborating with cross-functional teams to bring cutting-edge machine learning innovations into our systems.

• Design, develop, and optimize machine learning models for database query automation and voice-based interactions.
• Enhance the robotic dialogue flow by implementing NLP (Natural Language Processing) models for seamless user communication.
• Work with SQL and NoSQL databases to improve query efficiency and response time using AI-driven approaches.
• Develop speech recognition and text-to-speech models to facilitate natural voice interactions.
• Implement predictive analytics and recommendation systems to enhance user experience.
• Collaborate with software engineers, data scientists, and robotics experts to integrate AI models into existing systems.
• Train and fine-tune deep learning and reinforcement learning models for adaptive conversation flows.
• Monitor model performance, troubleshoot issues, and continuously refine algorithms.

• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field.
• Strong proficiency in Python, TensorFlow, PyTorch, and Scikit-learn.
• Experience with NLP frameworks such as spaCy, NLTK, or OpenAI GPT models.
• Knowledge of speech recognition technologies like DeepSpeech or Google Speech-to-Text API.
• Experience with database management and AI-driven query optimization.
• Familiarity with robotics frameworks such as ROS (Robot Operating System) is a plus.
• Strong analytical and problem-solving skills.
• Excellent teamwork and communication abilities.

• Experience in deploying AI models to production using Docker, Kubernetes, or cloud platforms (AWS, Azure, GCP).
• Hands-on experience with LLMs (Large Language Models) for advanced dialogue generation.
• Understanding of edge AI for deploying models on embedded systems or robotics hardware.

We are a group of professionals aiming to create a positive impact that makes a difference in mobility solutions. We are focused on developing unique solutions that fit the needs of customers across the industry verticals.

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.

World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.

As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle – from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.

You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments – such as product & tech, the core business verticals, trust & safety, finance and others – to enable them to be successful.

In this role, you will:

• Query large datasets with SQL and feed ML models.
• Perform data exploration to find patterns in the data and understand the state and quality of the data available.
• Utilize Python code for analyzing data and building statistical models to solve specific business problems.
• Evaluate ML models and fine tune model parameters considering the business problem behind.
• Collaborate with senior peers to Deploy ML models in production.
• Build customer-facing reporting tools to provide insights and metrics which track system performance.
• Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data
• Participate in the off-hours on call stability rotation to support live ML models

• Bachelor’s degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field.
• Statistical modelling and math
• Basic knowledge of Machine learning algorithms.
• Basic knowledge of SQL.
• Basic knowledge of visualization tools such as Periscope
• Excellent verbal and written communication.
• Strong problem solving skills.

• Ability to contribute to a platform used by more than 5M users in UAE and other platforms in the region.
• Strengthen your resume and build your network.
• Opportunity to find a full time career with the region's leading organization.
• Working in a multicultural environment with over 50 different nationalities
• Access to the Learning & Development tools and courses provided by the company.

Bayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

#dubizzle

EchoTwin AI is the intelligence layer powering self-healing cities—urban systems that not only detect issues in real time, but also trigger automated corrective actions or surface prioritized insights through agentic workflows. This represents a fundamental shift from reactive governance to proactive, adaptive urban management. The result? Cleaner, safer, smarter cities that manage themselves.

Our platform combines artificial intelligence, digital twins, and spatial analytics to help municipalities and infrastructure operators monitor assets, enforce compliance, and optimize urban operations. By integrating edge-based visual intelligence with real-time data and geospatial reasoning, EchoTwin AI delivers continuous oversight and faster, more intelligent responses to complex urban challenges.

With deployments across North America and the Middle East—including flagship projects in New York City, Abu Dhabi, and Riyadh—we partner with forward-thinking governments and innovators to build resilient, adaptive infrastructure for the cities of tomorrow.

• Collaborate with cross-functional teams, including the product manager, software developers, and domain experts.

• Research and experiment with state-of-the-art tools and techniques in Machine Learning.

• Document processes, pipelines, and model performance thoroughly.

• Train and deploy machine learning models for object detection and classification in images and videos.

• Preprocess and annotate image and video datasets for training purposes.

• ·Optimize deep learning models for efficiency and scalability in production.

• ·Design and implement predictive models to analyze trends, patterns, and anomalies.

• Develop data pipelines with data engineers to handle large-scale structured and unstructured datasets.

• Apply statistical and machine learning techniques to forecast outcomes and support decision-making.

• Master’s or Bachelor's degree in Computer Science, Mathematics, IT, or a related field.

• 5+ years of experience as a Computer Vision Engineer.

• 10+ years in software development and machine learning.

• Strong knowledge of machine learning concepts and algorithms.

• Proficiency in Python, C++, and ML libraries like TensorFlow or PyTorch.

• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.

• Experience in computer vision, particularly object detection and image processing techniques (e.g., YOLO).

• Familiarity with predictive analytics tools.

• Knowledge of cloud platforms (AWS) for deploying and managing machine learning models.

• Experience with MLOps practices.

• Proficiency in spoken and written English.

There are endless learning and development opportunities from a highly diverse and talented peer group, including experts in various fields, including Computer Vision, GenAI, Digital Twin, Government Contracting, Systems and Device Engineering, Operations, Communications, and more!

• Options for medical, dental, and vision coverage for employees and dependents (for US employees)

• Flexible Spending Account (FSA) and Dependent Care Flexible Spending Account (DCFSA)

• 401(k) with 3% company matching

• Unlimited PTO

• Profit sharing

Please do not forward resumes to our jobs alias, EchoTwin AI employees, or any other company location. EchoTwin AI is not responsible for any fees related to unsolicited resumes.

Messilat is seeking a talented MLOps Engineer for our client's team. The perfect candidate will excel in deploying models, managing microservices, utilizing Docker, and maintaining Kubernetes. Our client is also exploring AI applications in customer service, cybersecurity, and compliance.

Key Responsibilities

• Transition models from development to production, ensuring scalability and high performance. Collaborate with development teams for seamless model deployment.
• Implement monitoring and maintenance strategies for deployed models to ensure ongoing accuracy and reliability.
• Maintain Kubernetes clusters to ensure high availability and performance.
• Work with cross-functional teams to understand business requirements and deliver effective machine learning solutions.
• Develop and implement strategies that optimize efficiency and data quality.

Qualifications

• Minimum of 3 years of experience in MLOps or a related field.
• Expertise in model deployment, containerization, and orchestration (e.g., Docker, Kubernetes).
• Familiarity with cloud platforms (e.g., AWS, or on-premises) for model deployment and management.
• Experience in deploying AI models and managing their lifecycle.
• Proficiency in Python for scripting and automation.
• Prior experience in addressing scalability and pricing concerns in ML operations.

Skills

• Model deployment, monitoring, Docker, Kubernetes, AWS Cloud services, on-premises deployment, collaboration.

If you are passionate about MLOps and looking for a challenging role where you can make a significant impact, we would love to hear from you. Apply today!

Join to apply for the Machine Learning Engineer role at Helios Towers .

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French Language Expert and Senior Talent Acquisition Manager

Machine Learning Engineer

Location : Dubai, UAE

About Us : We are a leading independent telecoms infrastructure company, with one of the most extensive tower portfolios across Africa and the Middle East. Our business model promotes tower infrastructure sharing and enables mobile network operators to deliver connectivity more quickly, reliably, and cost-effectively, driving sustainable development in our markets.

Overview : Reporting to the Director of Digital Innovation, you will design, build, and deploy production-grade machine learning solutions, driving data-driven insights for our global tower-management platform.

Key Responsibilities :

• Ingest and preprocess structured / unstructured data (images, text, time series)
• Engineer and select features to maximize model performance
• Prototype and implement ML algorithms using TensorFlow, PyTorch, or scikit-learn
• Perform hyperparameter tuning, cross-validation, and model selection
• Define evaluation metrics (precision, recall, F1, ROC-AUC) and conduct A / B tests
• Build CI / CD pipelines for data, code, and model artifacts; automate retraining and rollback
• Monitor model performance, data drift, and system health; alert on anomalies
• Document model designs, data schemas, APIs, and runbooks

Experience & Skills :

• 3–5+ years delivering ML into production
• Hands-on with Python and ML libraries (TensorFlow, PyTorch, scikit-learn)
• MLOps tools : MLflow, Kubeflow; cloud deployment (AWS, Azure, GCP)
• Domain experience in computer vision, NLP, or forecasting
• Agile / Scrum collaboration; strong analytic and communication skills

Qualifications :

• Bachelor's / Master's in CS, Data Science, Statistics, or related
• Google Professional ML Engineer
• Proficiency in SQL, Git, Docker, and Kubernetes
• Competitive basic salary
• Discretionary bonus
• Health insurance
• Life insurance

Helios Towers is committed to promoting equal opportunities in employment. You and any job applicants will receive equal treatment regardless of age, disability, marital status, pregnancy or maternity, race, color, nationality, ethnic or national origin, religion, or belief.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Information Technology
• Telecommunications

J-18808-Ljbffr

About Us

EchoTwin AI is the intelligence layer powering self-healing cities—urban systems that not only detect issues in real time, but also trigger automated corrective actions or surface prioritized insights through agentic workflows. This represents a fundamental shift from reactive governance to proactive, adaptive urban management. The result? Cleaner, safer, smarter cities that manage themselves.

Our platform combines artificial intelligence, digital twins, and spatial analytics to help municipalities and infrastructure operators monitor assets, enforce compliance, and optimize urban operations. By integrating edge-based visual intelligence with real-time data and geospatial reasoning, EchoTwin AI delivers continuous oversight and faster, more intelligent responses to complex urban challenges.

With deployments across North America and the Middle East—including flagship projects in New York City, Abu Dhabi, and Riyadh—we partner with forward-thinking governments and innovators to build resilient, adaptive infrastructure for the cities of tomorrow.

Responsibilities

Collaborate with cross-functional teams, including the product manager, software developers, and domain experts.

Research and experiment with state-of-the-art tools and techniques in Machine Learning.

Document processes, pipelines, and model performance thoroughly.

Computer Vision

Train and deploy machine learning models for object detection and classification in images and videos.

Preprocess and annotate image and video datasets for training purposes.

• Optimize deep learning models for efficiency and scalability in production.

Predictive Analytics

Develop data pipelines with data engineers to handle large-scale structured and unstructured datasets.

Apply statistical and machine learning techniques to forecast outcomes and support decision-making.

Experience

Master's or Bachelor's degree in Computer Science, Mathematics, IT, or a related field.

5+ years of experience as a Computer Vision Engineer.

10+ years in software development and machine learning.

Strong knowledge of machine learning concepts and algorithms.

Proficiency in Python, C++, and ML libraries like TensorFlow or PyTorch.

Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.

Experience in computer vision, particularly object detection and image processing techniques (e.g., YOLO).

Familiarity with predictive analytics tools.

Knowledge of cloud platforms (AWS) for deploying and managing machine learning models.

Experience with MLOps practices.

Proficiency in spoken and written English.

Benefits and Perks

There are endless learning and development opportunities from a highly diverse and talented peer group, including experts in various fields, including Computer Vision, GenAI, Digital Twin, Government Contracting, Systems and Device Engineering, Operations, Communications, and more

Options for medical, dental, and vision coverage for employees and dependents (for US employees)

Flexible Spending Account (FSA) and Dependent Care Flexible Spending Account (DCFSA)

401(k) with 3% company matching

Unlimited PTO

Profit sharing

Please do not forward resumes to our jobs alias, EchoTwin AI employees, or any other company location. EchoTwin AI is not responsible for any fees related to unsolicited resumes.

J-18808-Ljbffr

EchoTwin AI is the intelligence layer powering self-healing cities—urban systems that not only detect issues in real time, but also trigger automated corrective actions or surface prioritized insights through agentic workflows. This represents a fundamental shift from reactive governance to proactive, adaptive urban management. The result? Cleaner, safer, smarter cities that manage themselves.

Our platform combines artificial intelligence, digital twins, and spatial analytics to help municipalities and infrastructure operators monitor assets, enforce compliance, and optimize urban operations. By integrating edge-based visual intelligence with real-time data and geospatial reasoning, EchoTwin AI delivers continuous oversight and faster, more intelligent responses to complex urban challenges.

With deployments across North America and the Middle East—including flagship projects in New York City, Abu Dhabi, and Riyadh—we partner with forward-thinking governments and innovators to build resilient, adaptive infrastructure for the cities of tomorrow.

• Collaborate with cross-functional teams, including the product manager, software developers, and domain experts.

• Research and experiment with state-of-the-art tools and techniques in Machine Learning.

• Document processes, pipelines, and model performance thoroughly.

• Train and deploy machine learning models for object detection and classification in images and videos.

• Preprocess and annotate image and video datasets for training purposes.

• ·Optimize deep learning models for efficiency and scalability in production.

• ·Design and implement predictive models to analyze trends, patterns, and anomalies.

• Develop data pipelines with data engineers to handle large-scale structured and unstructured datasets.

• Apply statistical and machine learning techniques to forecast outcomes and support decision-making.

• Master's or Bachelor's degree in Computer Science, Mathematics, IT, or a related field.

• 5+ years of experience as a Computer Vision Engineer.

• 10+ years in software development and machine learning.

• Strong knowledge of machine learning concepts and algorithms.

• Proficiency in Python, C++, and ML libraries like TensorFlow or PyTorch.

• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.

• Experience in computer vision, particularly object detection and image processing techniques (e.g., YOLO).

• Familiarity with predictive analytics tools.

• Knowledge of cloud platforms (AWS) for deploying and managing machine learning models.

• Experience with MLOps practices.

• Proficiency in spoken and written English.

There are endless learning and development opportunities from a highly diverse and talented peer group, including experts in various fields, including Computer Vision, GenAI, Digital Twin, Government Contracting, Systems and Device Engineering, Operations, Communications, and more

• Options for medical, dental, and vision coverage for employees and dependents (for US employees)

• Flexible Spending Account (FSA) and Dependent Care Flexible Spending Account (DCFSA)

• 401(k) with 3% company matching

• Unlimited PTO

• Profit sharing

Please do not forward resumes to our jobs alias, EchoTwin AI employees, or any other company location. EchoTwin AI is not responsible for any fees related to unsolicited resumes.

General Purpose

• We are looking for a highly skilled Machine Learning Engineer to join our team and contribute to the development of AI-powered solutions. The candidate should have expertise in Python programming, REST API development, cloud infrastructure, and AI model integration. This role requires strong problem-solving skills, a deep understanding of AI technologies, and the ability to optimize and deploy AI applications efficiently. The ideal candidate will have hands-on experience in building, deploying, and maintaining machine learning models and GenAI solutions using modern cloud platforms and MLOps practices. You will work closely with cross-functional teams to design scalable AI pipelines and integrate LLM-based solutions into production environments. You will play a critical role in building scalable, resilient, and secure data platforms that power analytics, AI, and data-driven innovation at Wynn.
  
  

• Design, implement, and maintain end-to-end ML pipelines using Databricks notebooks, Delta Lake, and MLflow for experiment tracking, model versioning, and lifecycle management.
• Leverage Databricks AutoML for rapid prototyping and efficient model selection in early-stage experimentation.
• Implement ML model deployment workflows using Databricks Jobs and manage serving endpoints with low-latency requirements.
• Design, develop, and deploy ML and GenAI solutions using Python and LLM frameworks.
• Build and deploy ML production systems, contributing to their design and ongoing maintenance
• Develop and maintain ML pipelines, manage the data lifecycle, and ensure data quality and consistency throughout
• Assure robust implementation of ML guardrails and manage all aspects of service monitoring
• Develop and deploy accessible endpoints, including web applications and REST APIs, while maintaining steadfast data privacy and adherence to security best practices and regulations
• Embrace agile development practices, valuing constant iteration, improvement, and effective problem-solving in complex and ambiguous scenarios
• Collaborate with cross-functional teams including architects, data engineers, analysts, and business leaders to deliver robust data solutions.
• Write and maintain infrastructure as code using YAML, Implement and manage CI/CD pipelines for ML workflows.
• Ensure model governance and compliance using protocols like Model Context Protocol and A2A Protocol.
• Produce comprehensive documentation including architectural diagrams, data flow maps, runbooks, and lineage tracking artifacts.
• Continuously improve ml pipeline efficiency by identifying performance bottlenecks and reducing compute/storage costs.
• Containerize applications using Docker and manage deployments on Azure
• Implement DevOps best practices in the data lifecycle, including CI/CD for pipelines, automated testing, and version control.
• Facilitate internal knowledge sharing via technical workshops, peer reviews, and training sessions for continuous team development.
  
  

• A bachelor's degree in computer science, information technology, or a related field is required; a master's degree is preferred but not mandatory.
• Minimum age 21.
  
  

• A minimum of 3-5 years of hands-on experience in Python software development with a focus on modular, scalable, and efficient coding for AI/LLM-based applications.
• Proven track record of building, scaling, and leading complex ML engineering platforms in enterprise environments.
• Strong experience designing and deploying cloud-native ML solutions on Azure Databricks, with an emphasis on scalable model training, model management using MLflow, and real-time inference.
• Demonstrated success in implementing AI agents or autonomous workflows using tools such as LangGraph, CrewAI, or similar frameworks.
• Experience in real-time or near-real-time inference systems and low-latency model serving.
  
  

• Hands-on experience with Databricks Machine Learning environment, including MLflow tracking, model registry, and production deployment workflows.
• Proficient in using Databricks Feature Store, AutoML, and real-time model inference using Databricks Serving or external endpoints.
• Familiarity with Databricks Unity Catalog and access control for secure ML asset management.
• Advanced proficiency in Python and LLM, with strong skills in performance tuning, modular coding, and automation scripting
• Experience deploying GenAI & related frameworks (e.g., LangChain, LLMOps, PaLM) use cases in Snowflake ecosystem
• Develop, optimize, and maintain scalable machine learning workflows and models using Databricks notebooks and MLflow.
• Understanding of how MCPs can complement structured Snowflake data to deliver rich narrative insights, automated clinical summaries, and patient engagement tools.
• Build AI-driven applications using Snowflake Cortex, Document AI, and Snowpark ML.
• Integrate GenAI tools like OpenAI GPT, Claude (Anthropic), and xAI's Grok to enhance unstructured data processing and generate intelligent summaries or decision recommendations.
• Experience in experimentation, feature engineering, Model registration, deployment, and monitoring, using AutoML cost and quota management
• Strong written and verbal communication skills in English, with the ability to influence, mentor, and align technical teams and stakeholders.
• Candidates with coursework or academic research in deep learning, reinforcement learning, or natural language processing are highly encouraged.
  
  

• Databricks Certified Machine Learning Professional
• Snowflake SnowPro Core Certification
• Azure Data Scientist Associate