Senior AI Infrastructure
6 hours ago
Role OverviewWe are seeking a highly skilled Senior AI Infrastructure & Platform Engineer to join our client's team in Riyadh. In this role, you'll be responsible for building, managing, and optimizing scalable AI infrastructure and compute environments that support high-performance workloads, including GPU-accelerated AI/ML pipelines, cluster scheduling, and orchestration. Key Responsibilities Deploy, maintain, and optimize GPU-based compute clusters and infrastructure. Manage and operate GPU orchestration tools and platforms such as: Nvidia Base Command Manager (critical) Nvidia AI Enterprise Suite Nvidia GPU and Network Operators Nvidia NIMs and Blueprints Configure, deploy, and maintain compute workloads using scheduling and orchestration tools including: Slurm (critical) Vanilla Kubernetes Install, configure, and maintain the underlying OS (e.g. Canonical Ubuntu) and supporting system software. Monitor and troubleshoot infrastructure performance, availability, and reliability; ensure high uptime for AI/ML workloads. Work with data scientists, ML engineers, and dev teams to define infrastructure requirements, resource allocation, and deployment workflows. Develop automation scripts, CI/CD pipelines, and best practices for infrastructure provisioning and management. Document architecture, configurations, and operational procedures; enforce security, compliance, and backup policies. RequirementsRequired Skills & Experience Proven experience managing GPU-based AI/ML infrastructure and compute clusters. Hands-on experience with: Nvidia Base Command Manager Nvidia AI Enterprise Suite Nvidia GPU/Network Operators, NIMs, Blueprints Strong experience with Slurm and/or Kubernetes orchestration. Solid Linux system administration skills — preferably on Ubuntu or similar distributions. Strong scripting/automation ability (e.g. Bash, Python, or relevant tooling) for provisioning, deployment, and maintenance. Excellent troubleshooting and performance-tuning skills. Experience collaborating with ML/data science teams and integrating infrastructure with their workflows. Strong understanding of networking, security, resource allocation, and cluster management best practices. Preferred Qualifications Previous experience working in a high-performance computing (HPC) or AI-focused infrastructure team. Knowledge of containerization, container orchestration, and GPUs in cloud or on-prem environments. Experience with CI/CD, infrastructure-as-code (e.g. Terraform, Ansible), monitoring tools, and logging setups. Familiarity with workload scheduling, job queuing, resource quotas, and GPU-shared environments.
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Senior AI Infrastructure
1 day ago
Delhi, Delhi, India DeepSource Technologies Full time ₹ 1,20,000 - ₹ 2,00,000 per yearRole OverviewWe are seeking a highly skilled Senior AI Infrastructure & Platform Engineer to join our client's team in Riyadh. In this role, you'll be responsible for building, managing, and optimizing scalable AI infrastructure and compute environments that support high-performance workloads, including GPU-accelerated AI/ML pipelines, cluster scheduling,...
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Senior AI Infrastructure
1 day ago
Delhi, Delhi, India DeepSource Technologies Full time ₹ 6,00,000 - ₹ 8,50,000 per yearRole OverviewWe are seeking a highly skilled Senior AI Infrastructure & Platform Engineer to join our client's team in Riyadh. In this role, you'll be responsible for building, managing, and optimizing scalable AI infrastructure and compute environments that support high-performance workloads, including GPU-accelerated AI/ML pipelines, cluster scheduling,...
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Senior NLP/AI Engineer
5 days ago
New Delhi, India Devnagri AI Full timeCompany Description Devnagri is an AI-powered translation platform on a mission to make content accessible to everyone by bridging linguistic gaps. The company enables businesses and key industries such as BFSI, Ed-tech, e-commerce, and OTT platforms to connect with a diverse audience. Devnagri delivers 5x faster and highly accurate translations to...
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Senior NLP/AI Engineer
6 days ago
New Delhi, India Devnagri AI Full timeCompany Description Devnagri is an AI-powered translation platform on a mission to make content accessible to everyone by bridging linguistic gaps. The company enables businesses and key industries such as BFSI, Ed-tech, e-commerce, and OTT platforms to connect with a diverse audience. Devnagri delivers 5x faster and highly accurate translations to...
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Senior AI Platform
1 week ago
New Delhi, India Norwin Technologies Full timeTitle: Senior AI Platform & Infrastructure EngineerLocation: BangaloreExperience: 8+ YearsWork Mode: HybridJob Description:Were looking for an experienced Infrastructure Engineer with a strong background in Kubernetes (K8s), GPU-based workloads, and scaling large distributed systems. We need builders, not just maintainers. Ideal candidates will have hands-on...
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Senior AI Platform
5 days ago
New Delhi, India Norwin Technologies Full timeTitle: Senior AI Platform & Infrastructure Engineer Location: Bangalore Experience: 8+ Years Work Mode: HybridJob Description: Were looking for an experienced Infrastructure Engineer with a strong background in Kubernetes (K8s), GPU-based workloads, and scaling large distributed systems. We need builders, not just maintainers. Ideal candidates will have...
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DevOps Specialist-AI Infrastructure
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New Delhi, India Word Works AI Full timeJob Title: Freelance DevOps EngineerCompany: Word Works AI Location: Hybrid Engagement: Freelance / Contract (Immediate Start) About Word Works AIWord Works AI is a fast-growing conversational AI startup building multilingual voice-based AI agents that help enterprises automate outreach, collections, and customer engagement. We’re scaling rapidly across...
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Senior AI Engineer
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Senior Software Engineer
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AI Infrastructure Architect
4 days ago
New Delhi, India The Adecco Group Full timeDesign and implement large-scale AI/ML infrastructure solutions using NVIDIA GPU clusters, SMCI server platforms, and high-performance computing architectures to support enterprise AI workloads Lead the architecture and deployment of distributed AI training environments, including multi-node GPU clusters, InfiniBand networking, and parallel computing...