MLOps Engineer بدوام كامل في أبوظبي
التخصص
متفرقات
نوع الدوام
دوام كامل
الخبرة
أي مستوى
الموقع
أبوظبي
وصف الوظيفة
About AI71AI71 builds secure, enterprise-ready AI applications for developers, businesses, governments, knowledge workers, and sector-specific users.The company focuses on responsible research and applying advanced AI to real-world challenges.The RoleOwn ML infrastructure and reliability strategy across AI71's platform.Define how LLMs and other deep learning models are deployed, fine-tuned, and served at scale.Own architecture decisions across SaaS and on-premises operating models.Mentor engineers across teams and drive multi-quarter ML infrastructure strategy.What You'll DoDefine ML infrastructure architecture covering model deployment with vLLM, Triton, or TGI; pipelines with MLflow or Kubeflow; and cloud-native infrastructure.Set reliability direction through monitoring, latency, throughput, availability targets, and incident response across research and production.Mentor senior MLOps engineers and improve operational standards across multiple teams.Drive initiatives that improve inference performance and cost efficiency, including distributed training frameworks.Partner with research, product, and engineering leadership on multi-quarter ML infrastructure strategy.Scale ML infrastructure across managed SaaS and fully air-gapped on-premises deployments.What You'll Bring10+ years of MLOps, ML infrastructure, or machine learning engineering experience with architectural ownership.Experience architecting large-scale LLM and ML infrastructure deployments.Deep AWS, Azure, or GCP expertise and strong Python proficiency.Mentorship experience developing engineers into independent higher-level contributors.Experience with managed SaaS and disconnected air-gapped ML systems.Architectural-depth Kubernetes expertise covering GPU scheduling, multi-tenancy, operators, and distributed workload failure modes.Strong communication, stakeholder management, and decision-making skills.Strong PreferencePlatform-level production reliability ownership, including SLOs, incident command, postmortems, and reliability improvement.Architecture-level distributed training and fine-tuning experience, including cluster design, checkpointing, and failure recovery.Deep GPU systems knowledge, including CUDA, NCCL, NVLink, and InfiniBand or RoCE.Portfolio-level model optimization experience with quantization or speculative decoding and measurable outcomes.Experience in regulated or security-constrained environments involving governance, lineage, audit, and secrets management.Experience maturing MLOps practices through standards, platform abstractions, and paved paths.Bare-metal GPU cluster architecture and scheduling with Slurm or Kubernetes.Nice to HaveConference speaking, technical writing, or industry thought leadership.Open-source contributions to inference, serving, or ML infrastructure projects.C/C++ or CUDA kernel experience for performance-critical paths.Arabic language skills.Why AI71Mission-driven work on AI applications for critical sectors.Opportunity to work with advanced models and resources on real-world challenges.Competitive compensation, benefits, and career growth opportunities.Flexible working environment with current tools and technologies.
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