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operation manager Jobs in Dubai United Arab Emirates

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ai ml operations mlops

INFRA ASSURE

Job PurposeManages machine learning pipelines, automates deployment, and ensures ongoing monitoring and maintenance of AI models.Key Responsibilities&middot; Develop and maintain CI/CD pipelines for ML models.&middot; Automate model training, testing, deployment, and monitoring.&middot; Implement tools for drift detection, model performance tracking, and retraining.&middot; Ensure reliability, scalability, and auditability of ML infrastructure.&middot; Collaborate with engineers and data scientists to ensure seamless deployment.Minimum QualificationsEducation: Bachelor of Computer Science, Master's in AI or Data Science is a plus.Experience: 3&ndash;5 yearsKey Competency RequirementsTechnical Skills:&middot; Expertise in MLOps tools (MLflow, TFX, Kubeflow).&middot; Experience with Kubernetes, Docker, and cloud platforms.Operational Skills:&middot; Automation of model lifecycle and monitoring workflows.&middot; Knowledge of version control and DevOps practices.Soft Skills:&middot; Attention to detail and proactive monitoring.&middot; Strong documentation and support capabilities.Job Type: Full-timeApplication Question(s):<ul><li>What is your current notice period or earliest joining date?</li><li>What are your salary expectations for this role?</li><li>Current location, nationality, and current job title/role?</li><li>Are you willing to work remotely ?</li><li>Have you worked with CI/CD pipelines specifically for machine learning model deployment?</li><li>Are you experienced with Kubernetes, Docker, and cloud platforms (AWS / Azure / GCP)?</li><li>Total years of experience in MLOps / ML Engineering?</li></ul>Education:<ul><li>Bachelor's (Preferred)</li></ul>Experience:<ul><li>MLOps tools such as MLflow, Kubeflow, TFX, or Airflow: 5 years (Preferred)</li></ul>Language:<ul><li>Arabic and English (Preferred)</li></ul>Location:<ul><li>Dubai (Preferred)</li></ul>

AI/ML Operations (MLOps)

iquasar software solutions

iQuasar Software Solutions is a purpose-driven company with a strong emphasis on &ldquo;People.&rdquo; We operate to empower people in the community we operate in. Listen in to our HR Manager explaining the hiring process that helps us to make a change in society by bringing the best talent and helping them grow professionally.
 <div><div>Senior Technical Lead &ndash; AI/ML &amp; MLOps
</div><div><div>Job Title: Senior Technical Lead &ndash; AI/ML &amp; MLOps 
Location: Srinagar 
Experience: 6&ndash;10 years overall (3&ndash;5 years in AI/ML &amp; MLOps) 
Education: Master&rsquo;s or above in AI/ML/Data Science or equivalent 
About the Role 
We are seeking a Senior Technical Lead &ndash; AI/ML &amp; MLOps to drive the design and implementation of advanced AI systems. The ideal candidate combines deep technical expertise with product vision and a high sense of ownership. 
You will lead efforts to assemble efficient AI toolchains, implement agentic AI frameworks, and integrate low-code/no-code solutions to accelerate time-to-market for AI-powered products. 
Key Responsibilities</div><ul><li>
Architect and lead AI/ML systems from concept to deployment.</li><li>
Build and optimize MLOps pipelines across AWS, Azure, and GCP.</li><li>
Implement and integrate agentic AI platforms (e.g., Copilot Studio, Microsoft AI Foundry, etc.) and low-code/no-code ecosystems.</li><li>
Assemble scalable AI toolchains to enhance productivity and automation.</li><li>
Collaborate cross-functionally with product, data, and engineering teams to deliver high-impact AI solutions.</li><li>
Engage with customers to understand their requirements and develop custom AI solutions within time and budget while meeting quality objectives</li><li>
Lead by example &mdash; mentor team members, ensure quality delivery, and drive continuous innovation.</li><li>
Take initiative to identify and integrate emerging AI technologies to improve outcomes.</li></ul><div>
Requirements</div><ul><li>
Proven experience in software development, with a strong focus on AI/ML and MLOps.</li><li>
Track record of successfully leading AI-driven products or large-scale ML projects.</li><li>
Proficiency in Python, TensorFlow/PyTorch, and modern DevOps/MLOps practices.</li><li>
Experience deploying models and services across AWS, GCP, and Azure.</li><li>
Familiarity with agentic AI, AI orchestration frameworks, and toolchain design.</li><li>
Strong communication skills, leadership qualities, and exceptional initiative.</li><li>
Ability to operate in a fast-paced, product-focused environment with end-to-end accountability.</li></ul></div></div><div></div>
 <div><div><div><div><div><div><div><div>WORK HARD AND BE YOURSELF
<h2 class="jobSectionHeader">Why Choose Us</h2>
</div></div></div></div><div><div><div><div><div><div><h3 class="jobSectionHeader">Leader&rsquo;s Support</h3>
</div></div><div><div><h3 class="jobSectionHeader">Great Team</h3>
</div></div><div><div><h3 class="jobSectionHeader">Knowledge Sharing</h3>
</div></div><div><div><h3 class="jobSectionHeader">Health Insurance</h3></div></div></div></div></div></div></div></div></div></div>

Senior Technical Lead – AI/ML & MLOps

Glow Beauty On Demand

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies

ML Platform Engineer Generative AI & Machine Learning Infrastructure

Job Title ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Job Description ML Platform Engineer Generative AI &amp; Machine Learning Infrastructure Location: Dubai, UAE Industry: Technology / AI / Food &amp; Q-commerce Function: Machine Learning Engineering Gender: Any Candidate Nationality: Any Job Type: Full-time Role Overview Talabat, the leading on-demand food and Q-commerce app in the region, is seeking an experienced ML Platform Engineer to design, develop, and scale robust machine learning and generative AI platforms. The role involves building end-to-end ML infrastructure, enabling fast experimentation, efficient model deployment, and seamless monitoring to support next-generation AI-driven solutions for millions of users. Key Responsibilities * Build scalable ML platforms supporting data ingestion, model training, deployment, and monitoring for both traditional ML and generative AI models * Design standardized ML workflows using tools like MLflow, Kubeflow, and implement CI/CD pipelines with Docker and Kubernetes * Optimize generative AI deployments involving transformers, embeddings, RAG systems, and vector databases such as Pinecone, Redis, or Weaviate * Implement real-time serving frameworks like TensorFlow Serving, NVIDIA Triton, or Seldon for production-grade inference * Automate model lifecycle management and implement observability measures to track performance, detect drift, and maintain reliability * Collaborate with data engineering and product teams to align ML infrastructure with strategic business goals * Drive cloud infrastructure integration using AWS or GCP services, including Kubernetes clusters, managed ML services, and serverless components * Ensure cost efficiency, performance optimization, and adherence to best practices for MLOps and generative AI workflows Qualifications and Experience * Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) * Minimum 3 years of experience in ML platform engineering, MLOps, or generative AI infrastructure roles * Expertise in Python, ML frameworks (TensorFlow, PyTorch), and APIs such as Hugging Face and LangChain * Hands-on experience with containerization, orchestration (Docker, Kubernetes), and infrastructure-as-code tools (Terraform, Helm) * Proven ability to build real-time inference pipelines integrated with feature stores and streaming platforms like Kafka or Kinesis * Familiarity with SQL for data processing and knowledge of observability tools for monitoring AI systems * Strong understanding of model optimization techniques including quantization, batching, and prompt-tuning strategies What We Offer * Opportunity to work on advanced ML and AI projects impacting millions of users in the Middle East * Competitive salary and benefits package * A collaborative, innovation-driven environment with cutting-edge tools and technologies * Career development in one of the fastest-growing tech ecosystems in the region

ML Platform Engineer Generative AI & Machine Learning

Ageless Medical Center

We are seeking an experienced and innovative AI Engineer to design, build, and deploy AI-driven solutions that enhance business operations and patient experience. The ideal candidate will have expertise in machine learning, natural language processing, and automation systems, with hands-on experience in developing and integrating AI models into production environments.Key Responsibilities<ul><li>Design, develop, and deploy AI/ML models and algorithms for business applications.</li><li>Build and maintain data pipelines for model training and validation.</li><li>Collaborate with software engineers, data scientists, and business teams to integrate AI capabilities into products and systems.</li><li>Apply deep learning, NLP, and computer vision techniques to solve real-world problems.</li><li>Optimize models for scalability, performance, and efficiency.</li><li>Analyze datasets to identify trends, anomalies, and predictive opportunities.</li><li>Stay updated with emerging AI technologies, frameworks, and best practices.</li><li>Prepare technical documentation and participate in project planning and progress reporting.</li><li>Ensure compliance with data security, governance, and ethical AI standards.</li></ul>Qualifications<ul><li>Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, AI, Data Science, or a related field.</li><li>3&ndash;6 years of experience in AI/ML model development, preferably within the UAE or GCC region.</li><li>Strong programming skills in Python and libraries such as TensorFlow, PyTorch, Keras, Scikit-learn.</li><li>Experience with cloud-based AI environments (AWS SageMaker, Google Vertex AI, Azure ML).</li><li>Solid understanding of data preprocessing, model evaluation, and deployment.</li><li>Familiarity with MLOps pipelines and version control tools (Git, Docker).</li><li>Excellent problem-solving, analytical, and teamwork skills.</li></ul>Job Type: Full-time

AI Engineer

Stellar Technologies

Key Responsibilities
<ul>
<li>Lead planning and execution of large-scale AI infrastructure and platform initiatives across Azure and hybrid environments.</li>
<li>Translate business and architecture goals into actionable project plans with measurable milestones and KPIs.</li>
<li>Manage dependencies across infrastructure, MLOps, and DevSecOps streams.</li>
<li>Oversee Agile delivery using Azure DevOps Boards or Jira (sprints, backlogs, release schedules).</li>
<li>Ensure secure and efficient delivery of GPU-accelerated compute and storage workloads.</li>
<li>Collaborate with architecture and engineering teams to align design, provisioning, and governance standards.</li>
<li>Implement and track compliance with Azure Policy, Azure Arc, and Key Vault integrations.</li>
<li>Review and validate infrastructure readiness for GPU and high-performance computing workloads.</li>
<li>Maintain project governance, budgets, and progress reports using Azure Cost Management and dashboarding tools.</li>
<li>Serve as the bridge between technical teams, business leadership, and vendors to ensure seamless execution.</li>
<li>Coordinate licensing, resourcing, and procurement with internal finance and operations teams.</li>
<li>Promote Agile and DevOps best practices, while mentoring project coordinators and engineers.</li>
<li>Lead post-project retrospectives and implement process improvements for future releases.</li>
</ul>
Required Knowledge &amp; Skills
<ul>
<li>Strong understanding of Microsoft Azure architecture and services including Azure Machine Learning, Azure Arc, Azure Policy, and Azure Monitor.</li>
<li>Experience with hybrid connectivity (VPN, ExpressRoute, private endpoints).</li>
<li>Broad knowledge of AI/ML, MLOps, and DevOps delivery models.</li>
<li>Familiarity with CI/CD, IaC (Terraform, Bicep), and cloud security governance.</li>
<li>Hands-on exposure to GPU-based or HPC workloads.</li>
<li>Deep understanding of project governance, Agile methodologies, and stakeholder communication.</li>
<li>Skilled in project tools like Azure DevOps Boards, Jira, Confluence, or Smartsheet.</li>
</ul>
Experience &amp; Certifications
<ul>
<li>8 12 years of experience in technical project or program management, preferably in AI/ML or cloud transformation.</li>
<li>Proven success in managing cross-functional engineering projects across infrastructure, data, and platform domains.</li>
</ul>
Preferred Certifications:
<ul>
<li>PMP / PMI-ACP</li>
<li>Azure Administrator / Azure Fundamentals</li>
<li>SAFe Agilist</li>
</ul>
Success Metrics (First 12 Months)
<ul>
<li>Successful rollout of the Enterprise AI Platform across Azure and hybrid infrastructure.</li>
<li>100% of AI/ML model deployments automated via CI/CD.</li>
<li>Improved deployment velocity and &gt;99% platform availability.</li>
<li>Full compliance with cost governance and resource optimization.</li>
<li>Executive dashboards implemented for KPIs and risk tracking.</li>
</ul>

Technical Project Manager Enterprise AI Platform

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