Staff MLOPs engineer

Discovered MENA; Abu Dhabi; On-site; AED 450,000 - 750,000; Full time

Benefits offered by this job

Relocation & visa support

Top-tier hardware

Tax-free salary

Comprehensive benefits

Job summary

Tanqeeb is hiring a Senior / Staff MLOps Engineer to own infrastructure, reliability, and deployment strategy for deep learning platforms. The role covers cloud SaaS and air-gapped on-prem environments, with leadership across Kubernetes and GPU scheduling.

The candidate should bring 10+ years in MLOps, proven LLM deployment experience, and hands-on work with on-prem and multi-cloud infra. Competitive relocation is provided for Abu Dhabi relocation.

Qualifications

• 10+ years in MLOps or ML Infrastructure with end-to-end architectural ownership.
• Proven track record deploying, fine-tuning, and serving LLMs at scale.
• Deep Kubernetes expertise (GPU scheduling, operators, multi-tenancy) and multi-cloud fluency.
• Hands-on experience with on-premises, bare-metal, or air-gapped ML environments.

Responsibilities

• Architect scalable model serving (vLLM, Triton, TGI), pipeline orchestration (MLflow, Kubeflow), and multi-cloud delivery (AWS, Azure, GCP).
• Drive latency, throughput, and cost optimizations using distributed training frameworks (DeepSpeed, FSDP, Megatron-LM).
• Build resilient ML infrastructure for cloud and secure, disconnected deployments.
• Set platform SLOs, incident response practices, and GPU cluster scheduling in Kubernetes.
• Mentor engineers, set standards, and collaborate on long-term infrastructure roadmaps.

Skills

MLOps architecture

LLM deployment

Kubernetes/GPU scheduling

Multi-cloud

On-prem ML infra

Tools

MLflow

Kubeflow

DeepSpeed

Megatron-LM

vLLM

Triton

TGI

Slurm

Job description

Hiring: Staff / Senior MLOps Engineer

Location: Abu Dhabi, UAE (Full Relocation Provided)

Role Type: Full-time | Senior / Staff Level

About the Company

Our client is a leading artificial intelligence organization building Global AI infrastructure with sovereign backing.

We are looking for a Senior / Staff MLOps Engineer to own the infrastructure, reliability, and deployment strategy for our deep learning platforms across both managed cloud SaaS and air-gapped on-premises environments.

Key Responsibilities

• Architect scalable model serving (vLLM, Triton, TGI), pipeline orchestration (MLflow, Kubeflow), and multi-cloud delivery (AWS, Azure, GCP).
• Drive latency, throughput, and cost optimizations using distributed training frameworks (DeepSpeed, FSDP, Megatron-LM).
• Build resilient ML infrastructure designed for both cloud and secure, disconnected deployments.
• Set platform SLOs, incident response practices, and GPU cluster scheduling strategies in Kubernetes.
• Mentor engineers, set engineering standards, and collaborate with research teams on long-term infrastructure roadmaps.

What You’ll Bring

• 10+ years in MLOps or ML Infrastructure with end-to-end architectural ownership.
• Proven track record deploying, fine-tuning, and serving LLMs at scale.
• Deep Kubernetes expertise (GPU scheduling, operators, multi-tenancy) and multi-cloud fluency.
• Hands-on experience with on-premises, bare-metal, or air-gapped ML environments.
• Strong preference for GPU systems depth (CUDA, NCCL, NVLink), quantization (FP8, AWQ), or Slurm cluster management.

What's on Offer

• Complete relocation, visa, and transition support to Abu Dhabi for candidates worldwide.
• Access to top-tier hardware, proprietary models, and high-stakes AI applications.
• Highly competitive tax-free salary and comprehensive benefits.