AI Ops Engineer | Talent Arabia | UAE

Tech Junction Ltd; United Arab Emirates; On-site; AED 260,000 - 420,000; Full time

Job summary

Talent Arabia in the UAE is seeking an experienced AI Ops Engineer to own operationalizing ML models, building automated deployment pipelines, and ensuring robust observability for production AI workloads. You will collaborate with data scientists, ML engineers, and cloud platform squads to guarantee resilience and low-latency inference.

Ideal candidates have a strong MSc/PhD-equivalent background in CS/AI, hands-on MLOps experience, and immediate availability.

Qualifications

• Bachelor’s or Master’s degree in CS/AI/Data Eng or related.
• 4+ years software engineering, with 2+ years in AI/ML ops in production.
• Proficiency with MLOps tools and orchestration (MLflow, Kubeflow, Airflow).
• Experience deploying AI workloads on AWS/Azure using Docker & Kubernetes.

Responsibilities

• Design, build, and maintain robust MLOps pipelines for production ML workloads.
• Manage end-to-end model deployment lifecycles, registries, and automated inference serving infrastructure.
• Configure monitoring, logging, and observability for AI models and data pipelines.
• Optimize model inference performance, GPU utilization, latency, and throughput in cloud environments.
• Implement CI/CD workflows for data science and AI deliverables.
• Collaborate with data scientists, ML engineers, and cloud architects.
• Ensure data privacy, governance standards, and security protocols.
• Maintain technical documentation, runbooks, and pipeline diagrams.
• Stay updated with emerging MLOps tools to improve infrastructure.

Skills

MLOps tools

Kubeflow

Airflow

Docker

Kubernetes

Python

Cloud platforms (AWS/Azure)

Education

Bachelor’s or Master’s degree in Computer Science, AI, Data Engineering or related

Tools

MLflow

Kubeflow

Airflow

Docker

Kubernetes

Triton Inference Server

Pinecone

Milvus

vLLM

Job description

Position Summary

Talent Arabia is seeking an experienced, highly technical, and accomplished AI Ops Engineer with extensive experience in artificial intelligence and machine learning (AI/ML) operations to join our client engagement team on a full-time, permanent basis in the UAE (candidates based in the UAE or willing to relocate). In this specialized MLOps and AI operations role, you will spearhead managing AI/ML model deployment lifecycles in production environments, building automated ML pipelines, and configuring comprehensive monitoring and observability platforms for AI workloads. You will work closely with data scientists, machine learning engineers, and cloud platform squads to guarantee model resilience and low-latency inference. Ideal candidates bring a robust academic degree in computer science, deep practical mastery of MLOps frameworks, and immediate availability.

Detailed Job Description

As an AI Ops Engineer at Talent Arabia in the UAE, you will take full ownership of operationalizing machine learning models, managing automated deployment pipelines, and ensuring robust observability for production AI workloads. Your day-to-day responsibilities encompass building and maintaining MLOps pipelines, integrating model serving frameworks, configuring monitoring telemetry across cloud platforms, and resolving inference bottlenecks. You will collaborate with data scientists and software engineers to transition experimental models into highly scalable production services. Working in a fast-paced technology consulting environment, you will drive artificial intelligence operational excellence.

Key Responsibilities

• Design, build, and maintain robust MLOps and AI Ops pipelines for production machine learning workloads.
• Manage end-to-end model deployment lifecycles, model registries, and automated inference serving infrastructure.
• Configure comprehensive monitoring, logging, and observability platforms tailored for AI/ML models and data pipelines.
• Optimize model inference performance, GPU utilization, latency, and throughput in cloud production environments.
• Implement continuous integration and continuous delivery (CI/CD) workflows specifically for data science and AI deliverables.
• Collaborate proactively with data scientists, machine learning engineers, and cloud platform architects.
• Troubleshoot complex model drift, data quality anomalies, and inference failure incidents promptly.
• Ensure strict compliance with data privacy regulations, model governance standards, and security protocols.
• Maintain comprehensive technical documentation, model operational runbooks, and pipeline architecture diagrams.
• Stay abreast of emerging tools in the MLOps ecosystem to continuously improve infrastructure capabilities.

Required Qualifications & Skills

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Engineering, or a related technical discipline.
• Minimum 4+ years of professional software engineering experience, with 2+ years specializing in AI/ML operations and production environments.
• Strong technical proficiency in MLOps/AI Ops tools, workflow orchestration (MLflow, Kubeflow, Airflow), and automation frameworks.
• Solid hands-on experience deploying AI workloads across cloud platforms (AWS, Azure) utilizing Docker and Kubernetes.
• Proven expertise in monitoring, observability, logging, and performance tuning for machine learning systems.
• Strong analytical problem-solving capabilities and collaborative communication skills.
• Professional availability for employment in the UAE or willingness to relocate (Application email: [e-mail]).

Nice-to-Have Skills

• Professional certifications in cloud architecture or machine learning engineering.
• Hands-on familiarity with vector databases (Pinecone, Milvus) and LLM serving frameworks (vLLM, Triton Inference Server).
• Prior working experience in artificial intelligence research labs, high-growth tech startups, or enterprise IT consultancy firms.
• Advanced programming proficiency in Python, Bash, and SQL.
• Bilingual proficiency in Arabic and English.

Application Information

• Recruiter: Talent Arabia Recruitment Team
• Contact Name: Biman Saha (Business Coordinator)
• Email: [e-mail]
• Phone: Unspecified
• Application URL: Unspecified
• Salary/Rate: Competitive and commensurate with experience
• Deadline: Open until filled
• Notice Period: Immediate to short notice preferred
• Contract Duration: Permanent / Full-Time (UAE / Relocation supported)

Recruitment Pro Tip

When applying for AI Ops and MLOps roles, ensure your resume explicitly highlights your MLflow/Kubeflow pipeline scale, GPU inference optimization experience, and model observability stack.