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machine learning intern

Confidential Company

<ul><li>Develop and deploy machine learning models for real-world applications, from data collection to model serving, ensuring scalability and efficiency.</li><li>Collaborate with cross-functional teams (data scientists, software engineers, product managers) to understand business needs and translate them into machine learning solutions.</li><li>Design and implement end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.</li><li>Experiment with various machine learning algorithms, frameworks, and tools to identify the best solutions for specific problems, optimizing for performance and accuracy.</li><li>Write clean, well-documented, and testable code (Python, etc.) and contribute to code reviews, ensuring code quality and maintainability.</li><li>Monitor and maintain deployed machine learning models, addressing performance issues, retraining models with new data, and ensuring continuous improvement.</li></ul>

Machine Learning Engineer

Almosafer

We are seeking a talented Machine Learning Engineer to join our data science team. The ideal candidate will be responsible for developing and implementing machine learning models and algorithms that solve complex business problems. You will work closely with data scientists, software engineers, and stakeholders to deliver scalable solutions.
Responsibilities:
<ul>
<li>Design, build, and deploy machine learning models and algorithms.</li>
<li>Collaborate with data scientists to refine data features and enhance model performance.</li>
<li>Optimize and improve existing machine learning models for efficiency and accuracy.</li>
<li>Conduct data preprocessing, feature engineering, and data analysis.</li>
<li>Monitor and maintain models in production to ensure they operate effectively.</li>
<li>Document and communicate model designs and performance metrics to stakeholders.</li>
<li>Stay updated on the latest industry trends and advancements in machine learning and AI.</li>
<li>Participate in code reviews and contribute to a culture of continuous improvement</li>
</ul>
Preferred Skills:
<ul>
<li>Familiarity with version control systems (e.g., Git) and CI/CD practices.</li>
<li>Experience with AI/GenAI</li>
<li>Experience with AWS data services (e.g., AWS EMR, AWS Glue, AWS Athena)</li>
<li>Design/build and deploy API services</li>
</ul>

Specialist - Machine Learning

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 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

Luxoft

Work directly with computer vision perception engineers, and camera ISP engineers.
Define the image quality requirements for customer use cases
Develop image processing algorithms to optimizing the camera image quality for performance improvement of computer vision applications
Develop custom ML models for visual recognition and training it from scratch
Quantization and pruning the ML models
Data evaluation using relevant metrics to increase the model performance
Implement computer vision/image processing algorithms in fast/optimal C++ code
Implement heuristic/math algorithms and probabilistic methods for camera AI
Research existing C++ solutions for CV logic
Develop cross platform C++ code
Cover algorithms and CV code with unitest
Ramp up on new technologies related to CV/ML/algorithms (not R&amp;D)
Integrate machine learning modules into algorithms

Lead Machine Learning, Computer Vision Software Engineer

Mondia

<div>
 Be part of shaping how AI transforms how we work. You'll scout emerging AI technologies, pilot new tools, and coordinate cross-departmental adoption projects. A key focus will be managing and enhancing our internal Knowledge Hub &mdash; ensuring information flows seamlessly and employees can leverage AI to its fullest.
 
 
 
 What you will do!
 
 
 
 <ul>
 <li>
 Roll out AI tools and features company-wide to boost adoption and measurable value
 </li>
 <li>
 Identify and evaluate emerging AI technologies with potential business impact
 </li>
 <li>
 Drive employee engagement and training to maximize AI tool utilization
 </li>
 <li>
 Lead the program management and evolution of the company Knowledge Hub
 </li>
 <li>
 Enhance Knowledge Hub performance through LLM integration for smarter, easier interactions
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 BA Degree in Artificial Intelligence, Computer Science, Data Science, or Information Systems
 </li>
 <li>
 Coursework or certifications in AI tools, prompt engineering, or machine learning fundamentals (e.g., Coursera, Google AI, Microsoft Learn)
 </li>
 <li>
 Ability to analyze adoption metrics, feedback, and performance data
 </li>
 <li>
 Proficiency in tools like Excel, Google Sheets, or Power BI/Tableau (nice-to-have)
 </li>
 <li>
 Curiosity to link data insights with business impact
 </li>
 <li>
 Generative AI platforms (OpenAI, Anthropic, Gemini, etc.)
 </li>
 <li>
 Productivity &amp; collaboration tools (Notion, Miro, Slack, Microsoft 365)
 </li>
 <li>
 Knowledge bases (Confluence, Guru, SharePoint)
 </li>
 <li>
 Project management tools (Asana, Trello, Jira)
 </li>
 <li>
 Data visualization tools (Power BI, Tableau &mdash; optional)
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 Opportunity to work for a dynamic international company with a flat hierarchical structure, where your voice matters and your impact is seen.
</div>

AI Transformation Intern

Etihad Credit Bureau

<div>
 
 
 JOB DESCRIPTION SUMMARY
 
 
 
 
 
 
 The Machine Learning Engineer role will specialise in maintaining scoring models, production system maintenance and high-availability operations. You'll orchestrate and maintain our AzureML/Databricks-based scoring engine, ensure 99.99% uptime for production models, perform emergency fixes, and manage QA/UAT processes. This role partners with data scientists to operationalize models and data engineers to ensure efficient data flows.
 
 
 
 
 
 
 KEY DUTIES &amp; RESPONSIBILITIES
 
 
 <ul>
 <li>
 
 Production Model Maintenance:
 
 Monitor, troubleshoot, and rectify issues in deployed credit scoring models (e.g., score drift, feature misalignment, output anomalies).
 </li>
 <li>
 
 Platform Orchestration:
 
 Manage AzureML pipelines &amp; Databricks workflows for model retraining, batch scoring, and real-time inference.
 </li>
 <li>
 
 High-Availability Engineering:
 
 Ensure 24/7 uptime of scoring APIs serving banking clients; implement failover systems and load balancing.
 </li>
 <li>
 
 Release Management:
 
 Oversee QA/UAT processes for model updates including back-testing, shadow deployments, and canary releases.
 </li>
 <li>
 
 Model Governance:
 
 Maintain audit trails for model versions, inputs/outputs, and performance metrics. Support Compliance and Audit with creation of logs when requested.
 </li>
 <li>
 
 Incident Response:
 
 Lead troubleshooting of scoring engine failures with SLAs for financial institution clients.
 </li>
 <li>
 
 Infrastructure Optimization:
 
 Tune AzureML/Databricks clusters for cost-performance efficiency at scale.
 </li>
 <li>
 
 Vendor Management:
 
 Ensure vendor support is completing work as per scope and SLAs. Rectifying any vendor delivery issues.
 </li>
 </ul>
 
 
 
 
 
 EDUCATION &amp; SKILLS
 
 
 <ol>
 <li>
 Educated with at least bachelor&rsquo;s degree or equivalent in related field
 </li>
 <li>
 Education specialization or master&rsquo;s degree in computer science, Software Engineering
 </li>
 <li>
 Proficient in English
 </li>
 <li>
 Preferred proficiency in Arabic
 </li>
 <li>
 In-depth knowledge of React Native and Next JS and related modules, components and libraries
 </li>
 <li>
 Preferred In-depth knowledge of SiteCore or experience integrating with SiteCore
 </li>
 </ol>
 
 
 
 
 
 EXPERIENCE &amp; KNOWLEDGE
 
 
 <ol>
 <li>
 Bachelor's/Master's in Computer Science, Engineering, Data Science, or related field
 </li>
 <li>
 2+ years in Data Science or Software Engineering experience
 </li>
 <li>
 2+ years production ML operations experience, MLOps lifecycle management, including monitoring, retraining, and model versioning.
 </li>
 <li>
 Strong problem-solving skills and the ability to resolve issues efficiently.
 </li>
 <li>
 CI/CD for ML systems using tools such as Azure DevOps, GitHub Actions, MLflow, and other similar tools
 </li>
 <li>
 Ability to adapt ML workflows across different cloud environments (Azure, AWS, GCP) as needed.
 </li>
 </ol>
 
 
 
 
 
 ABILITIES &amp; SPECIFIC REQUIREMENTS
 
 
 <ol>
 <li>
 Practical experience in cloud-based ML platforms such as AzureML, Databricks, or equivalent (e.g., SageMaker, Vertex AI), with a preference for Azure.
 </li>
 <li>
 Python/PySpark for model debugging and patching. Working knowledge of Scikit-Learn and NumPy
 </li>
 <li>
 Deep understanding of credit scoring systems: feature engineering, scorecard interpretation, and output validation
 </li>
 <li>
 Credit bureau data structures (tradelines, inquiries, public records)
 </li>
 <li>
 Model risk management (MRM) standards
 </li>
 <li>
 Azure Solutions Architect or MLOps certifications
 </li>
 <li>
 Experience with financial services-grade SLAs (99.9% uptime) and outage management
 </li>
 <li>
 Knowledge of containerization (Docker, Kubernetes, AKS, or similar orchestration tools)
 </li>
 <li>
 Practical experience with Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS) / Azure Blob Storage
 </li>
 <li>
 Knowledge of new and upcoming AI tools
 </li>
 <li>
 This is contained within the earlier requirement of python. If the plan is for this resource
 </li>
 <li>
 Excellent written and verbal communication skills English
 </li>
 <li>
 Strong interpersonal skills with the ability to engage and build relationships
 </li>
 <li>
 Crisis management under pressure
 </li>
 <li>
 Cross-functional collaboration with data science/risk teams
 </li>
 <li>
 Strong organizational skills with the ability to manage multiple tasks and projects simultaneously.
 </li>
 <li>
 Ability to develop and document procedures, roles, and guidelines.
 </li>
 <li>
 
 Security and Compliance
 
 Especially in financial services, mention data security, PII handling, and compliance with regulations
 </li>
 </ol>
</div>

Machine Learning Engineer (Contract - For Immediate Hire)

Explore 1758+ Machine learning intern in Dubai United Arab Emirates this November. Find roles across top companies and apply now to boost your career.