148 Machine Learning Engineer jobs in the United Arab Emirates

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

2 days ago Be among the first 25 applicants

Ready to embark on a journey where your growth is intertwined with our commitment to making a positive impact? Join the Delphi family - where Growth Meets Values.

At Delphi Consulting Pvt. Ltd. , we foster a thriving environment with a hybrid work model that lets you prioritize what matters most. Interviews and onboarding are conducted virtually, reflecting our digital-first mindset . We specialize in Data, Advanced Analytics, AI, Infrastructure, Cloud Security , and Application Modernization , delivering impactful solutions that drive smarter, efficient futures for our clients.

About the Role : We are looking for a highly skilled Machine Learning Engineer with a strong MLOps focus and hands-on experience with Databricks to join our dynamic team. The ideal candidate will play a key role in managing end-to-end ML pipelines, deploying models in a production-grade Databricks environment, and ensuring smooth collaboration across a remote, cross-functional team.

What you'll do :

• Design, develop, and manage ML pipelines within the Databricks ecosystem.
• Deploy, monitor, and retrain ML models in production.
• Work with Python , PySpark , Spark , and SQL for large-scale data processing and model development.
• Build and manage CI / CD pipelines in Azure DevOps for seamless model and code deployments.
• Develop and maintain LLM agents using diverse data sources including databases and knowledge graphs in a Databricks environment.
• Collaborate closely with remote data engineers , backend developers , and frontend developers to integrate ML models into applications.
• Perform code reviews and contribute to code quality standards.
• Create clear and concise documentation to track pipeline and model performance.

What you'll bring :

• 2–3 years of hands-on experience with Databricks , including ML and data pipeline management.
• 1–2 years of experience building AI / LLM agents that connect with Databricks.
• Strong proficiency in Python , SQL , PySpark / Spark .
• 3+ years of experience with Git for version control and collaboration.
• 1–3 years of experience deploying machine learning models in production environments using Databricks.
• 2+ years of DevOps experience , ideally in cloud environments.

What We Offer :

At Delphi, we are dedicated to creating an environment where you can thrive, both professionally and personally. Our competitive compensation package, performance-based incentives, and health benefits are designed to ensure you're well-supported. We believe in your continuous growth and offer company-sponsored certifications, training programs , and skill-building opportunities to help you succeed.

We foster a culture of inclusivity and support, with remote work options and a fully supported work-from-home setup to ensure your comfort and productivity. Our positive and inclusive culture includes team activities, wellness and mental health programs to ensure you feel supported.

Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

Consulting and Information Technology

Referrals increase your chances of interviewing at Delphi Consulting Middle East by 2x

Sign in to set job alerts for “Machine Learning Engineer” roles.

Data Scientist -AI and Generative AI (GenAI)

Software Engineer - Applied ML (Middle East)

Data Scientist II - Analysis (Analytics Engineering)

Data Scientist and Generative AI & Data Analytics

Software Test Engineer - QA Engineer - $70k - AI and Creator Tools

Global Village, Dubai, United Arab Emirates 6 months ago

Data Scientist, United Arab Emirates - BCG X

Software Development Engineer in Test (SDET)

Global Village, Dubai, United Arab Emirates 2 months ago

Data Scientist - AI and Advanced Analytics | Real Estate | AFET

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

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
  

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.

WE are hiring for our client a Machine Learning Engineer.

Desired Candidate Profile

This role involves utilizing Python to create machine learning algorithms for data analysis and statistical modeling. The focus is on problem-solving and collaborating with teams to innovate and drive projects forward. The company culture encourages taking ownership of tasks and projects to ensure successful outcomes. The position requires a strong foundation in technical skills and the ability to apply them in real-world scenarios. Working closely with colleagues, the role involves leveraging machine learning techniques to extract insights and make data-driven decisions. The ideal candidate will thrive in a dynamic and collaborative environment, continuously learning and adapting to stay at the forefront of machine learning advancements.

Company Industry

• IT - Software Services

Department / Functional Area

• IT Software

Keywords

• Data Science
• Python Programming

Disclaimer: Naukrigulf.com is only a platform to bring jobseekers & 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

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.

This is a remote position.

We represent a technology player whose digital banking platform is transforming financial services in emerging markets making a real impact by embedding credit and savings products into the digital channels people use every day. Their data-driven technology powers MNOs, fintechs, and banks, enabling them to scale fast and drive financial inclusion for millions. For those looking to work on cutting-edge financial tech with real-world impact, this is the opportunity for you.

With rapid growth, industry recognition, and a team that thrives on innovation, this is a chance to shape the future of finance in high-growth markets across Africa.

Our client is seeking an exceptional Machine Learning Engineer (Foundation Models Focus) to develop and scale AI and machine learning initiatives across their financial services ecosystem. This role is pivotal in driving AI-powered decision-making automation and hyper-personalization using foundation models including LLMs and multimodal AI. The Machine Learning Engineer will be responsible for developing pretraining, fine-tuning, and optimizing foundation models while working closely with data scientists, data engineers, and software engineering teams to deploy scalable AI solutions. This position plays a key role in enhancing financial AI applications such as automated underwriting, fraud detection, credit scoring, and AI-powered customer engagement, ensuring measurable improvements in performance and customer experience.

• Evaluate scope and support the foundation models and Generative AI strategy including potential applications in automated underwriting, alternative credit scoring, AI-powered customer interactions, fraud detection, and early-warning models.
  
• Design and develop AI-powered applications including chatbots, virtual assistants, personalized recommendation systems, and AI-driven decision-making tools.
  
• Plan for resourcing, training, and roadmap for AI adoption ensuring alignment with senior management and business needs.
  

• Pretrain, fine-tune, and optimize foundation models (e.g. GPT, LLaMA, Mistral) for various financial applications.
  
• Hyperparameter tuning for efficiency (e.g. optimization of transformer architectures, Mixture of Experts (MoE), retrieval-augmented generation (RAG)).
  
• Implement foundation model scaling techniques such as DeepSpeed, FSDP, and quantization to enhance efficiency.
  
• Develop custom embeddings, tokenizers, and retrieval models for enhanced financial NLP and multimodal tasks.
  
• Build pipelines for prompt engineering, reinforcement learning with human feedback (RLHF), and model alignment.
  

• Work with engineering and data teams to ensure AI models deployment is scalable, secure, and cost-efficient.
  
• Develop efficient inference optimization strategies using ONNX, TensorRT, and Triton Inference Server.
  
• Implement MLOps best practices including model versioning, continuous monitoring, retraining, and deployment on on-premise infrastructure or cloud (AWS, GCP, Azure).
  
• Define best practices for data collection, storage, and pipeline automation to enable AI-driven insights in financial services.
  

• Collaborate with data governance teams to ensure AI models comply with data privacy laws.
  
• Deploy real-time AI anomaly detection models to mitigate fraud risks in digital transactions.
  
• Partner with compliance teams to develop AI-driven regulatory reporting tools and automated risk alerts.
  
• Ensure ethical AI and bias mitigation techniques are integrated into foundation model-based decision-making systems.
  

• Develop AI models for hyper-personalized financial services based on behavioral analysis and customer interactions.
  
• Implement AI-powered marketing segmentation, dynamic customer scoring, and next-best-action recommendation engines.
  
• Partner with AI research institutions, universities, and fintech accelerators to drive foundation models and generative AI innovation.
  
• Represent the company at global fintech and AI summits, shaping industry conversations on Generative AI in financial services.
  
• Publish AI research, case studies, and thought leadership content to establish the company as a leader in AI-driven fintech.
  

What it takes to succeed:

• 7 years of experience in AI/ML, deep learning, NLP, or applied machine learning with at least 3 years leading AI teams.
  
• Strong expertise in foundation models, LLM architectures, and generative AI.
  
• Hands-on experience with AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers, DeepSpeed, MegatronLM).
  
• Experience in scaling AI/ML models using distributed computing frameworks (Ray, Spark, Dask).
  
• Proven ability to deploy and optimize foundation models in production including quantization, distillation, and efficient inference strategies.
  
• Strong knowledge of data governance, AI ethics, and regulatory compliance (GDPR, financial regulations).
  
• Experience working with vector databases (FAISS, Pinecone, Chroma) for retrieval-augmented generation (RAG).
  
• Familiarity with MLOps tools (MLflow, Kubeflow, Weights & Biases).
  
• Strong programming skills in Python, SQL, and cloud platforms (AWS, GCP, Azure).
  
• Ability to translate AI innovations into business-driven AI strategies for financial services.
  

As a Machine Learning Engineer at Aspire, you will play a key role in building intelligent systems that automate and optimize document understanding processes. You will be responsible for designing, developing, and deploying machine learning models focused on extracting structured data from complex, unstructured documents. Your skills in Python, deep learning, and natural language processing will help power intelligent automation solutions used across global financial operations.

As a Machine Learning Engineer at Aspire, you will play a key role in building intelligent systems that automate and optimize document understanding processes. You will be responsible for designing, developing, and deploying machine learning models focused on extracting structured data from complex, unstructured documents. Your skills in Python, deep learning, and natural language processing will help power intelligent automation solutions used across global financial operations.

• Design and implement intelligent document processing pipelines using a blend of machine learning and rule-based methods.
• Research and apply state-of-the-art deep learning models (e.g., transformers) for document parsing and semantic understanding.
• Develop and fine-tune large language models (LLMs) for tasks such as information extraction, table detection, and document classification.
• Build robust data validation frameworks to ensure accuracy and reliability of extracted information.
• Convert complex document formats into structured data while preserving context and content fidelity.
• Deploy models and ML pipelines to cloud infrastructure using tools like Docker and AWS services.
• Evaluate model performance through experiments, track key metrics, and communicate results to stakeholders.
• Participate in Agile development processes including sprint planning, daily stand-ups, and retrospectives.
• Collaborate with cross-functional teams including engineers, product managers, and domain experts.

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related discipline.
• 3-4 years of professional experience in Python development, with a focus on data extraction and ML applications.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras.
• Familiarity with transformer-based architectures and LLMs for NLP and document processing tasks.
• Proficiency in using the Hugging Face ecosystem (Transformers, Datasets, Model Hub).
• Solid SQL skills for querying and managing structured data.
• Strong problem-solving and analytical thinking skills.
• Excellent communication skills for translating technical concepts to non-technical audiences.
• Experience working in Agile/Scrum teams.
• Awareness or knowledge of IT security best practices as defined by ISO/SOC or similar.