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Glow Beauty On Demand

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

ML Platform Engineer

Dimension Data / NTT ltd

<div> <b>Key responsibilities:</b> <ul> <li>Provides support to users/administrators of the company platform.</li> <li>Supports and contributes to the growth of best practices for delivery of support services.</li> <li>Ensures understanding of company platform, Cloud technologies and troubleshooting practices to ensure successful resolution of challenging technical situations.</li> <li>Acts as a customer advocate, prioritizing and managing assigned incidents and escalations in queue with little or no supervision.</li> <li>Engages with the cross functional teams such as operations and engineering to build, drive and improve tools and processes for quicker issue resolution.</li> <li>Mentors less experienced team members in the various technologies.</li> <li>Performs any other related task as required.</li> </ul> </div> <br> <div> <b>To thrive in this role, you need to have:</b> <ul> <li>Seasoned working knowledge of the components in cloud/web applications.</li> <li>Seasoned understanding network monitoring connectors such as SCOM, Solarwinds etc.</li> <li>Seasoned understanding of SNMP traps and MIBs/OIDs.</li> <li>Seasoned understanding and ability to modify basic XML, JSON, Regular Expressions (RegEx).</li> <li>Seasoned understanding of the HTTP/HTTPS Request and Response Cycle.</li> <li>Seasoned understanding of database concepts.</li> <li>Seasoned understanding of ITSM, CMDB and ITIL business process.</li> <li>Excellent troubleshooting/root cause isolation skills.</li> <li>Must be proficient with analyzing log files and standard debugging concept.</li> <li>Seasoned familiarity with tools and practices of the trade such as incident management, knowledgebase, defect and escalation management.</li> <li>Seasoned understanding of email infrastructure/protocols.</li> <li>Seasoned understanding of Web Services   REST and SOAP and Authentication mechanisms   Single Sign-on, LDAP.</li> <li>Must have basic object-oriented programming skills (Java strongly preferred).</li> <li>Excellent written and verbal communication skills with the ability to clearly articulate solutions to technical problems.</li> <li>Ability to multi-task and work with high-value customer administrators and developers.</li> <li>Should be a team player working efficiently in a collaborative environment.</li> <li>Strong personal commitment to quality and customer service.</li> <li>Proven ability to maintain a professional demeanor when handling complex user issues.</li> </ul> </div>

Security Platform Engineer

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

ML Platform Engineer Generative AI & Machine Learning

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

ML Platform Engineer Generative AI & Machine Learning Infrastructure

myZoi

<div><span style="font-size: 11px;">About the Role</span></div><div><span style="font-size: 11px;">We're looking for a talented DevOps, DBA and SRE Engineer to join myZoi and help ensure our cloud-native, regulated fintech application maintains excellent reliability, performance, and security. In this role, you'll bridge the gap between development and operations, implementing robust automation, monitoring, and incident response processes that support our mission of financial inclusion.</span></div><div><span style="font-size: 11px;"><br></span></div><div><span style="font-size: 11px;">Key Responsibilities</span></div><div><span style="font-size: 11px;">Design, implement, and maintain infrastructure as code for our cloud-native platform on AWS</span></div><div><span style="font-size: 11px;">Create and optimize CI/CD pipelines for reliable, consistent deployments using Argo, GitHub, Jenkins, Sonar and other best of breed tooling</span></div><div><span style="font-size: 11px;">Implement comprehensive monitoring and alerting systems to ensure platform health</span></div><div><span style="font-size: 11px;">Drive incident management processes and conduct thorough postmortems</span></div><div><span style="font-size: 11px;">Collaborate with development teams to improve application reliability and performance</span></div><div><span style="font-size: 11px;">Establish SLOs/SLIs and track reliability metrics</span></div><div><span style="font-size: 11px;">Work on Continuous Improvement SRE and TechOps processes and rituals</span></div><div><span style="font-size: 11px;">Implement security best practices and ensure compliance with financial regulations</span></div><div><span style="font-size: 11px;">Automate routine operational tasks to improve efficiency and reduce human error</span></div><div><span style="font-size: 11px;">Contribute to capacity planning and cost optimization efforts</span></div><div><span style="font-size: 11px;">Configure and maintain our Datadog and CloudWatch observability stack across AWS environments</span></div><div><span style="font-size: 11px;">Design and implement custom metrics, dashboards, and alerts in Datadog to provide visibility into system health</span></div><div><span style="font-size: 11px;">Establish effective log management and analysis workflows to support troubleshooting</span></div><div><span style="font-size: 11px;">Manage complex multi-account infrastructure and access best-practices</span></div><div><span style="font-size: 11px;">Manage complex networking configuration</span></div><div><span style="font-size: 11px;">Manage AWS infrastructure including EKS, RDS, DirectConnect, Dynamo, Control Tower</span></div><div><span style="font-size: 11px;">Required Skills &amp; Experience</span></div><div><span style="font-size: 11px;">8+ years of experience in SRE, DevOps, or platform engineering roles</span></div><div><span style="font-size: 11px;">Strong knowledge of cloud platforms (AWS) and containerization technologies</span></div><div><span style="font-size: 11px;">Knowledge os AWS Networking, VPCs, Peering, Security Groups, MPLS, VPN</span></div><div><span style="font-size: 11px;">Experience with infrastructure as code tools (Terraform, CloudFormation, or equivalent)</span></div><div><span style="font-size: 11px;">Proficiency in at least one programming/scripting language (Python, Go, or TypeScript preferred)</span></div><div><span style="font-size: 11px;">Experience implementing and maintaining CI/CD pipelines, ArgoCD, Github, Jenkins</span></div><div><span style="font-size: 11px;">Strong understanding of monitoring tools and observability practices</span></div><div><span style="font-size: 11px;">Hands-on experience with Datadog for infrastructure monitoring, APM, and log management</span></div><div><span style="font-size: 11px;">Knowledge of security principles for cloud-native applications</span></div><div><span style="font-size: 11px;">Experience with container orchestration systems (Kubernetes)</span></div><div><span style="font-size: 11px;">Background in incident management and problem resolution</span></div><div><span style="font-size: 11px;">Experience with AWS CloudWatch metrics and integration with third-party observability platforms</span></div><div><span style="font-size: 11px;">Experience in Agile delivery, Jira, Confluence</span></div><div><span style="font-size: 11px;"><br></span></div><div><span style="font-size: 11px;">Preferred Qualifications</span></div><div><span style="font-size: 11px;">Experience working with fintech or other regulated applications</span></div><div><span style="font-size: 11px;">Knowledge of financial compliance requirements (e.g., PCI DSS, CISv8)</span></div><div><span style="font-size: 11px;">Experience implementing Zero Trust security models</span></div><div><span style="font-size: 11px;">Familiarity with service mesh technologies</span></div><div><span style="font-size: 11px;">Background in performance optimization and capacity planning</span></div><div><span style="font-size: 11px;">Experience with chaos engineering principles</span></div><div><span style="font-size: 11px;">Advanced Datadog skills, including creating custom agents and integrations</span></div><div><span style="font-size: 11px;">Experience implementing distributed tracing across microservices</span></div><div><span style="font-size: 11px;">Experience with Jira</span></div>

DevOps and DBA Engineer

Fuse Energy

<div>
 At Fuse, we're building a fully integrated energy company, from developing solar, wind, and hydrogen to power trading &amp; distributed energy installations. We sell directly to energy consumers, cutting out the middleman to reduce costs and pass on savings to customers.
 <br/>
 <br/>
 But we're not stopping there.
 <br/>
 <br/>
 We're also building the Energy Network: a decentralized network of smart devices where users get rewarded in Energy Dollars for electrifying their homes, shifting usage to off-peak hours, and helping balance the grid. The energy network helps the grid achieve energy stability, a crucial requirement for growth of AI data centers and energy intensive industries.
 <br/>
 <br/>
 We've raised $90M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group, and strategic angels like Nico Rosberg, co-founder of Solana, and GPs behind Meta, Revolut, Spotify, Uber, and more.
 <br/>
 <br/>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 As the Head of Engineering (Platform) at Fuse Energy, you will lead the development of our core backend systems and platform infrastructure, forming the technical foundation that powers all our products and services. You will own the architecture and scalability of the platform, ensuring we build robust, high-performance systems that enable rapid product iteration and exceptional customer experiences.
 <br/>
 <br/>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Own the backend platform architecture, infrastructure, and foundational services
  </li>
  <li>
   Drive the evolution of our platform to support scale, performance, and reliability
  </li>
  <li>
   Build a real-time digital twin of renewable generation and customer demand
  </li>
  <li>
   Design and manage high-volume data pipelines for energy consumption and system telemetry
  </li>
  <li>
   Lead the development of integration layers and messaging interfaces with third-party services
  </li>
  <li>
   Establish engineering best practices for observability, CI/CD, testing, and scalability
  </li>
  <li>
   Partner closely with product and backend teams to support rapid development cycles
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Proven track record as a senior software engineer or tech lead, ideally with platform/backend focus
  </li>
  <li>
   5+ years experience in software engineering, with 2+ years in a leadership role
  </li>
  <li>
   Experience building and operating production-grade systems at scale
  </li>
  <li>
   Strong understanding of system design, distributed computing, and cloud infrastructure
  </li>
  <li>
   Clear and proactive communication, with the ability to align cross-functional teams
  </li>
  <li>
   Hands-on approach to solving problems and making strategic decisions
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Bonus
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience with Infrastructure as Code (e.g., AWS CDK, Terraform)
  </li>
  <li>
   Experience with event-driven architecture, messaging queues, or stream processing
  </li>
  <li>
   Familiarity with building internal platforms or developer tooling
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary and a stock options sign-on bonus
  </li>
  <li>
   Biannual bonus scheme
  </li>
  <li>
   Fully expensed tech to match your needs!
  </li>
  <li>
   Paid annual leave
  </li>
  <li>
   Breakfast and dinner for office based employees
  </li>
 </ul>
</div>


Head of Engineering (Platform)

Careem

<div><div><p>Careem is building the Everything App for the greater Middle East &mdash; making it easy to move around, order food and groceries, manage payments, and more. Our purpose is simple: to simplify and improve people&rsquo;s lives and build an awesome organisation that inspires.<br>
Since 2012, Careem has enabled earnings for over 2.5 million Captains, simplified the lives of more than 70 million customers, and built a platform where the region&rsquo;s best talent and entrepreneurs thrive. We operate in 70+ cities across 10 countries, from Morocco to Pakistan.</p>
<p><b><i>
We&rsquo;re now entering our next chapter &mdash; one powered by AI. We&rsquo;re looking for AI talent: curious problem-solvers who know how to apply AI to build tools, automate workflows, and create real impact. Whether it&rsquo;s streamlining operations, enhancing customer experience, or reimagining internal systems &mdash; we want people who can make Careem work smarter and move faster.</i></b></p></div><div><h3 class="jobSectionHeader"><b>
About the team:</b></h3>
<p>
The AI Acceleration Office builds the intelligence layer that powers Careem&rsquo;s ecosystem, and we are looking for a Senior Software Engineer to drive architecture and development of it. Our mission is to drive competitive value through an Agentic AI Platform, a system that can design, orchestrate, and manage autonomous AI agents across customer and operational journeys.</p>
<h3 class="jobSectionHeader"><b>
About the role:</b></h3>
<p>
As a Senior Software Engineer, you&rsquo;ll lead the architecture and development of the AI Agent Creation and Management Platform, an intelligent layer that enables scalable agent creation, orchestration, lifecycle management, and performance monitoring. You&rsquo;ll work across<b> </b>backend systems, AI infrastructure, and data orchestration, designing abstractions that connect LLMs, context, memory, and state into real-time adaptive agents. This is a hands-on leadership role, you&rsquo;ll design systems, ship code, mentor engineers, and influence Careem&rsquo;s long-term AI platform strategy.</p>
<h3 class="jobSectionHeader"><b>
What you&rsquo;ll do:</b></h3>
<ul>
<li><p>Architect and implement the foundational services for Careem&rsquo;s Agentic AI Platform, covering agent creation APIs, orchestration pipelines, state machines, and monitoring layers.</p>
</li>
<li><p>Design abstractions for multi-agent collaboration, memory persistence, and reasoning cycles integrated.</p>
</li>
<li><p>Build scalable orchestration frameworks (LangGraph, or custom) that coordinate model calls, context injection, and multi-turn workflows across internal and external agents.</p>
</li>
<li><p>Develop observability and governance systems for AI agents: tracing, metrics, auditing, and self-healing.</p>
</li>
<li><p>Integrate LLM-based and retrieval-augmented components into backend services with strict latency, reliability, and compliance requirements.</p>
</li>
<li><p>Work with data scientists and ML engineers to operationalize models (embedding stores, vector databases, evaluation pipelines, model versioning).</p>
</li>
<li><p>Establish standards for agent safety, lifecycle management, and deployment reliability across Careem&rsquo;s product ecosystem.</p>
</li>
<li><p>Mentor engineers and shape platform-wide engineering practices around AI integration and distributed systems design.</p>
</li>
</ul><h3 class="jobSectionHeader"><b>What you&rsquo;ll need:</b></h3>
<ul>
<li><p>6+ years of backend or distributed systems engineering experience, with 2&ndash;3 years in AI/ML infrastructure or LLM-based systems.</p>
</li>
<li><p>Deep hands-on experience in Python and Go, with production experience in building scalable, event-driven architectures.</p>
</li>
<li><p>Expertise in orchestration and distributed compute (Kubernetes).</p>
</li>
<li><p>Experience in building end-to-end event-drive architecture and data pipelines (Kafka, Airflow and Flink)</p>
</li>
<li><p>Familiarity with agentic frameworks (LangGraph, LangChain, AutoGen) and design of multi-agent or RAG systems.</p>
</li>
<li><p>Experience in integrating LLMs and vector stores (FAISS, Pinecone, Weaviate, Milvus) into backend applications.</p>
</li>
<li><p>Solid understanding of model and agent observability, monitoring, and continuous evaluation.</p>
</li>
<li><p>Strong architectural skills, capable of designing systems that balance scalability, cost, and experimentation velocity.</p>
</li>
<li><p>Experience working with data streaming, metrics, and real-time feedback loops.</p>
</li>
<li><p>Growth mindset and bias for ownership, you thrive in high-autonomy, fast-paced, and purpose-driven environments.</p>
</li>
</ul><h3 class="jobSectionHeader"><b>What we&rsquo;ll provide you:</b></h3>
<p>
We offer colleagues the opportunity to drive impact in the region while they learn and grow. As a full time Careem colleague, you will be able to:</p>
<ul>
<li>Work and learn from great minds by joining a community of inspiring colleagues.</li>
<li>Put your passion to work in a purposeful organisation dedicated to creating impact in a region with a lot of untapped potential.</li>
<li>Explore new opportunities to learn and grow every day.</li>
<li>Work 4 days a week in office &amp; 1 day from home, and remotely from any country in the world for 30 days a year with unlimited vacation days per year. (If you are in an individual contributor role in tech, you will have 2 office days a week and 3 to work from home.)</li>
<li>Access to healthcare benefits and fitness reimbursements for health activities including gym, health club, and training classes.</li></ul></div></div><p></p>

Senior Software Engineer II - AI Platform

Explore 2004+ Platform engineer in Dubai this October. Find roles across top companies and apply now to boost your career.