199 Azure AI Engineer jobs in the United Arab Emirates

Join to apply for the Machine Learning Engineer role at AI71 .

About AI71: AI71 is an industry leader in artificial intelligence, delivering innovative solutions that empower developers, businesses and governments to solve complex challenges. AI71 builds secure, enterprise-ready applications powered by cutting-edge technology—tailored for knowledge workers and sector-specific needs. AI71 bridges the gap between advanced AI and real-world impact. Guided by a strong commitment to research and responsibility, we create transformative solutions that drive progress and empower communities.

As a Senior Machine Learning Engineer at AI71, you'll be responsible for developing, deploying, and optimizing machine learning models and systems that power our AI solutions. You will collaborate with cross-functional teams to translate business challenges into impactful AI products.

• Model Development: Develop, train, and deploy predictive models that enhance the capabilities of our AI solutions.
• AI Technologies: Work with state-of-the-art AI techniques, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), and apply them to real-world business contexts.
• Cross-Functional Collaboration: Partner with business stakeholders to understand objectives and translate them into actionable machine learning tasks.
• Model Optimization: Continuously monitor, evaluate, and improve models based on real-world performance and evolving business needs.
• Data Pipeline Maintenance: Implement and manage robust data preprocessing pipelines to ensure high-quality, reliable input data for model development.

• 5+ years of experience in AI, Machine Learning, Reinforcement Learning (RL), Data Science, or a related field.
• Proven experience with Large Language Models (LLMs) and fine-tuning techniques.
• Master's or Ph.D. in AI, Data Science, Computer Science, Statistics, or a related field.
• Strong proficiency in programming languages like Python or R. Preference for candidates with a competitive coding background (e.g., ACM/ICPC, NOI/IOI, Top Coder, Kaggle).
• Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch), Generative AI technologies, and libraries like Langchain, Weaviate, Langgraph, LlamaIndex.
• Demonstrated success in applying data science and machine learning to solve real-world, business-critical problems.
• Excellent communication and collaboration skills with the ability to work across interdisciplinary teams.
• Strong communication, stakeholder management, and decision-making skills, with a passion for building diverse, inclusive engineering teams.

• Mission-Driven Work: Work on cutting-edge AI applications with a talented and passionate team, solving real-world challenges in critical sectors.
• Unparalleled Opportunity: This is a chance to innovate and solve real-world challenges using AI at a company with unique access to world-leading models and resources.
• Career Growth: We offer competitive compensation, benefits, and significant career growth opportunities as a foundational member of the team.
• World-Class Environment: Enjoy a flexible working environment and the latest tools & technologies needed to do your best work.

• Mid-Senior level

• Full-time

• Engineering and Information Technology

• Technology, Information and Internet

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.

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

Get AI-powered advice on this job and more exclusive features.

Direct message the job poster from Helios Towers.

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

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
  
  

Job Summary:

Our client is seeking a highly skilled Machine Learning Platform Engineer to join their team in Dubai. As a Machine Learning Platform Engineer, you'll design, develop, and maintain scalable machine learning platforms and infrastructure to support our business objectives.

Key Responsibilities:

1. Design and develop machine learning platforms and infrastructure
2. Build and maintain scalable data pipelines and architectures
3. Collaborate with cross-functional teams to integrate machine learning models with business applications
4. Develop and implement automated testing and deployment scripts
5. Ensure platform security, scalability, and reliability

Requirements:

1. Bachelor's degree in Computer Science, Engineering, or related field
2. 3 years of experience in machine learning platform development
3. Proficiency in programming languages such as Python, Java, or C
4. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch)
5. Strong understanding of data structures, algorithms, and software design patterns

We are looking for a skilled and innovative Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and data-driven solutions that improve business outcomes. You will work closely with data scientists, software engineers, and product teams to turn data into actionable intelligence.

• Design and implement machine learning algorithms and models for various applications.

• Preprocess, clean, and analyze large datasets from diverse sources.

• Collaborate with cross-functional teams to define project requirements and success metrics.

• Train, test, and evaluate model performance using industry-standard metrics.

• Optimize models for scalability and real-time deployment.

• Deploy models into production using tools like Docker, Kubernetes, or cloud services (AWS, Azure, GCP).

• Monitor and maintain deployed models for accuracy and performance.

• Document code, models, and processes for future reference.

• Bachelor's or Masters degree in Computer Science, Engineering, Mathematics, or related field.

• Proven experience with Python and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.

• Strong understanding of machine learning algorithms, data structures, and software engineering principles.

• Experience with SQL and NoSQL databases.

• Familiarity with cloud platforms and MLOps practices.

• Excellent problem-solving and analytical skills.

• Strong communication and teamwork abilities.

• Ph.D. in a related field.

• Experience in deep learning, NLP, computer vision, or recommendation systems.

• Experience with tools like MLflow, Airflow, or Kubeflow.

• Contributions to open-source ML projects or published research papers.

Job Summary:

Our client is seeking a highly skilled Machine Learning Platform Engineer to join their team in Dubai. As a Machine Learning Platform Engineer, you'll design, develop, and maintain scalable machine learning platforms and infrastructure to support our business objectives.

Key Responsibilities:

• Design and develop machine learning platforms and infrastructure
• Build and maintain scalable data pipelines and architectures
• Collaborate with cross-functional teams to integrate machine learning models with business applications
• Develop and implement automated testing and deployment scripts
• Ensure platform security, scalability, and reliability

Requirements:

• Bachelor's degree in Computer Science, Engineering, or related field
• 3 years of experience in machine learning platform development
• Proficiency in programming languages such as Python, Java, or C
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch)
• Strong understanding of data structures, algorithms, and software design patterns

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

Get AI-powered advice on this job and more exclusive features.

Direct message the job poster from Helios Towers.

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

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